Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems | Paper Citation Record

Observation 442575f4-d49e-4537-b3f1-2e7c62c4d4b8 · outbound

This paper cites Adageo: Adaptive geometric learning for optimization and sampling.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Adageo: Adaptive geometric learning for optimization and sampling

Reference 1

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This paper cites A model-free version of the fundamental theorem of asset pricing and the super-replication theorem.Mathemati- cal Finance, 26(2):233–251.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A model-free version of the fundamental theorem of asset pricing and the super-replication theorem.Mathemati- cal Finance, 26(2):233–251

Reference 2

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This paper cites Bayesian posterior sampling via stochastic gradient fisher scoring.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Bayesian posterior sampling via stochastic gradient fisher scoring

Reference 3

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This paper cites Stochastic gradient mcmc for state space models.SIAM Journal on Mathematics of Data Science, 1(3):555–587.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Stochastic gradient mcmc for state space models.SIAM Journal on Mathematics of Data Science, 1(3):555–587

Reference 4

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This paper cites Physics-informed information field theory for modeling physical systems with uncertainty quantification.Journal of Computational Physics, 486:112100.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Physics-informed information field theory for modeling physical systems with uncertainty quantification.Journal of Computational Physics, 486:112100

Reference 5

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This paper cites Efficient optimal transport algorithm by accelerated gradient descent.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Efficient optimal transport algorithm by accelerated gradient descent

Reference 6

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This paper cites Wasserstein distributionally robust estimation in high dimensions: Performance analysis and optimal hyperparameter tuning.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Wasserstein distributionally robust estimation in high dimensions: Performance analysis and optimal hyperparameter tuning

Reference 7

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This paper cites Distributional Uncertainty Propagation via Optimal Transport.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Distributional Uncertainty Propagation via Optimal Transport

Reference 8

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This paper cites Deep learning and optimisation for quality of service modelling.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Deep learning and optimisation for quality of service modelling

Reference 9

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This paper cites On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case.Bernoulli, 27(1):1–33.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case.Bernoulli, 27(1):1–33

Reference 10

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This paper cites Sensitivity of multiperiod optimization problems with respect to the adapted Wasserstein distance.SIAM J.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Sensitivity of multiperiod optimization problems with respect to the adapted Wasserstein distance.SIAM J

Reference 11

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This paper cites Computational aspects of robust optimized certainty equivalents and option pricing.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Computational aspects of robust optimized certainty equivalents and option pricing

Reference 12

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This paper cites Sensitivity analysis of Wasserstein distributionally robust optimization problems.Proc.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Sensitivity analysis of Wasserstein distributionally robust optimization problems.Proc

Reference 13

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This paper cites Duality theory for robust utility maximisation.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Duality theory for robust utility maximisation

Reference 14

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Observation cd940ec2-8721-4c2f-b320-3e99f44ca5de · outbound

This paper cites Sensitivity of robust optimization problems under drift and volatility uncertainty.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Sensitivity of robust optimization problems under drift and volatility uncertainty

Reference 15

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This paper cites Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis

Reference 16

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This paper cites Data-driven non-parametric robust control under dependence uncertainty.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Data-driven non-parametric robust control under dependence uncertainty

Reference 17

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This paper cites Equilibria under knightian price uncertainty.Econometrica, 87 (1):37–64.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Equilibria under knightian price uncertainty.Econometrica, 87 (1):37–64

Reference 18

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This paper cites Estimation and uncertainty quantification for the output from quantum simulators.Foundations of Data Science, 1(2):157–176.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Estimation and uncertainty quantification for the output from quantum simulators.Foundations of Data Science, 1(2):157–176

Reference 19

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This paper cites Robust distortion risk measures.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust distortion risk measures

Reference 20

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Observation f7b53f1d-2d69-4e99-97e4-8e1d9c7f8f93 · outbound

This paper cites Models for minimax stochastic linear optimization problems with risk aversion.Mathematics of Operations Research, 35(3):580–602.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Models for minimax stochastic linear optimization problems with risk aversion.Mathematics of Operations Research, 35(3):580–602

Reference 21

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This paper cites Scaling up dynamic topic models.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Scaling up dynamic topic models

Reference 22

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This paper cites Multiple-priors optimal investment in discrete time for unbounded utility function.The Annals of Applied Probability, 28(3):1856–1892.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Multiple-priors optimal investment in discrete time for unbounded utility function.The Annals of Applied Probability, 28(3):1856–1892

Reference 23

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This paper cites Quantifying distributional model risk via optimal transport.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Quantifying distributional model risk via optimal transport

Reference 24

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This paper cites On distributionally robust extreme value analysis.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On distributionally robust extreme value analysis

Reference 25

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This paper cites Arbitrage and duality in nondominated discrete-time models.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Arbitrage and duality in nondominated discrete-time models

Reference 26

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This paper cites Langevin algorithms for very deep neural networks with application to image classification.Procedia Computer Science, 222:303–310.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Langevin algorithms for very deep neural networks with application to image classification.Procedia Computer Science, 222:303–310

Reference 27

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This paper cites Langevin algorithms for markovian neural networks and deep stochastic control.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Langevin algorithms for markovian neural networks and deep stochastic control

Reference 28

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This paper cites The promises and pitfalls of stochastic gradient Langevin dynamics.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems The promises and pitfalls of stochastic gradient Langevin dynamics

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.293220Z

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Observation 6455fd67-dec9-49ea-a4c7-3d93da73ac83 · outbound

This paper cites Viability and arbitrage under knightian uncertainty.Econometrica, 89(3):1207–1234.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Viability and arbitrage under knightian uncertainty.Econometrica, 89(3):1207–1234

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.289954Z

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Observation 6b245499-4d62-4f2c-802e-3dd695876775 · outbound

This paper cites The robust superreplication problem: a dynamic approach.SIAM Journal on Financial Mathematics, 10(4):907–941.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems The robust superreplication problem: a dynamic approach.SIAM Journal on Financial Mathematics, 10(4):907–941

Reference 31

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This paper cites On stochastic gradient langevin dynamics with dependent data streams: The fully nonconvex case.SIAM Journal on Mathematics of Data Science, 3(3):959–986.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On stochastic gradient langevin dynamics with dependent data streams: The fully nonconvex case.SIAM Journal on Mathematics of Data Science, 3(3):959–986

Reference 32

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This paper cites On the convergence of stochastic gradient mcmc algorithms with high-order integrators.Advances in neural information processing systems, 28.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On the convergence of stochastic gradient mcmc algorithms with high-order integrators.Advances in neural information processing systems, 28

Reference 33

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This paper cites Distributionally robust linear and discrete optimization with marginals.Operations Research, 70(3):1822–1834.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Distributionally robust linear and discrete optimization with marginals.Operations Research, 70(3):1822–1834

Reference 34

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This paper cites A robust learning approach for regression models based on distributionally robust optimization.Journal of Machine Learning Research, 19(13):1–48.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A robust learning approach for regression models based on distributionally robust optimization.Journal of Machine Learning Research, 19(13):1–48

Reference 35

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This paper cites On stationary-point hitting time and ergodicity of stochastic gradient Langevin dynamics.Journal of Machine Learning Research.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On stationary-point hitting time and ergodicity of stochastic gradient Langevin dynamics.Journal of Machine Learning Research

Reference 36

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Observation f6c33344-716b-4529-b2f0-8e9c428a3d5f · outbound

This paper cites Duality formulas for robust pricing and hedging in discrete time.SIAM Journal on Financial Mathematics, 8(1):738–765.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Duality formulas for robust pricing and hedging in discrete time.SIAM Journal on Financial Mathematics, 8(1):738–765

Reference 37

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Observation 05686ffd-873e-4187-a662-b77fde6a83df · outbound

This paper cites Martingale optimal transport duality.Mathematische Annalen, 379:1685–1712.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Martingale optimal transport duality.Mathematische Annalen, 379:1685–1712

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Observation 93532e9e-9dd2-4f76-8d84-50a9bb20b33b · outbound

This paper cites Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.617059Z

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Observation 056558cf-e4ba-4313-ad19-0a747643b7eb · outbound

This paper cites Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Further and stronger analogy between sampling and optimization: Langevin Monte Carlo and gradient descent

Reference 40

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Observation 6ab9dff2-4789-468b-8b2e-f6158742c4be · outbound

This paper cites User-friendly guarantees for the Langevin monte carlo with inaccurate gradient.Stochastic Processes and their Applications, 129(12):5278–5311.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems User-friendly guarantees for the Langevin monte carlo with inaccurate gradient.Stochastic Processes and their Applications, 129(12):5278–5311

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.249288Z

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Observation af139661-92b3-44a6-99fc-4ca27cf72ac6 · outbound

This paper cites Distributionally robust optimization under moment uncertainty with application to data-driven problems.Operations research, 58(3):595–612.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Distributionally robust optimization under moment uncertainty with application to data-driven problems.Operations research, 58(3):595–612

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.242523Z

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Observation 137f29b5-a58b-4a61-b720-d6f9a2009cc0 · outbound

This paper cites An adaptively weighted stochastic gradient mcmc algorithm for monte carlo simulation and global optimization.Statistics and Computing, 32(4):58.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems An adaptively weighted stochastic gradient mcmc algorithm for monte carlo simulation and global optimization.Statistics and Computing, 32(4):58

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.238887Z

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Observation f17c2b8b-705e-4a38-9986-87737d746406 · outbound

This paper cites A theoretical framework for the pricing of contingent claims in the presence of model uncertainty.The Annals of Applied Probability, 16(2):827 – 852.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A theoretical framework for the pricing of contingent claims in the presence of model uncertainty.The Annals of Applied Probability, 16(2):827 – 852

Reference 44

Resolution: verified exact; doi, observed 2026-05-24T02:43:47.343832Z

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Observation c88809a3-f376-480c-85c9-02bd7ec078da · outbound

This paper cites Martingale optimal transport and robust hedging in continuous time.Probability Theory and Related Fields, 160(1-2):391–427.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Martingale optimal transport and robust hedging in continuous time.Probability Theory and Related Fields, 160(1-2):391–427

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.227915Z

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Observation c855a05a-cd1b-457b-aeb6-76b603e3450d · outbound

This paper cites Robust hedging with proportional transaction costs.Finance and Stochastics, 18:327–347.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust hedging with proportional transaction costs.Finance and Stochastics, 18:327–347

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.205998Z

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Observation 2b8660df-7f7b-4900-8f2c-da1113af8367 · outbound

This paper cites Analysis of Langevin Monte Carlo via convex optimization.The Journal of Machine Learning Research, 20(1):2666–2711.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Analysis of Langevin Monte Carlo via convex optimization.The Journal of Machine Learning Research, 20(1):2666–2711

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.202412Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6ca40da0-def0-4771-b56e-750c7d9c47bb · outbound

This paper cites Robust risk aggregation with neural networks.Mathematical finance, 30(4):1229–1272.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust risk aggregation with neural networks.Mathematical finance, 30(4):1229–1272

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.198610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e016624f-706b-439a-9894-48638fe837a8 · outbound

This paper cites Risk, ambiguity, and the savage axioms.The quarterly journal of economics, 75 (4):643–669.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Risk, ambiguity, and the savage axioms.The quarterly journal of economics, 75 (4):643–669

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.191223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 69b63754-fe4a-4257-a8ff-5258258fdd3b · outbound

This paper cites Intertemporal asset pricing under knightian uncertainty.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Intertemporal asset pricing under knightian uncertainty

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.187412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e9bf0882-056b-4959-b3ae-9f24884b2fcc · outbound

This paper cites Time-independent generalization bounds for sgld in non- convex settings.Advances in Neural Information Processing Systems, 34:19836–19846.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Time-independent generalization bounds for sgld in non- convex settings.Advances in Neural Information Processing Systems, 34:19836–19846

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.183917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8b212eaf-8908-4519-97d6-b089f0f79627 · outbound

This paper cites Portfolio optimization with ambiguous correlation and stochastic volatilities.SIAM Journal on Control and Optimization, 54(5):2309– 2338.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Portfolio optimization with ambiguous correlation and stochastic volatilities.SIAM Journal on Control and Optimization, 54(5):2309– 2338

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.180132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e173afac-51d9-4911-aab9-317133f1fccc · outbound

This paper cites Variationally inferred sampling through a refined bound.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Variationally inferred sampling through a refined bound

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.176184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5a353c72-9344-493a-ba8e-61238bc44947 · outbound

This paper cites Distributionally robust stochastic optimization with Wasserstein distance.Mathematics of Operations Research, 48(2):603–655.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Distributionally robust stochastic optimization with Wasserstein distance.Mathematics of Operations Research, 48(2):603–655

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.172329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 43274e90-a98f-4ac2-84b8-93f5bb47b09f · outbound

This paper cites Wasserstein distributionally robust optimization and variation regularization.Oper.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Wasserstein distributionally robust optimization and variation regularization.Oper

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.168932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1699f324-31e1-4c3a-bb16-293150f47112 · outbound

This paper cites Maxmin expected utility with non-unique prior.Journal of mathematical economics, 18(2):141–153.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Maxmin expected utility with non-unique prior.Journal of mathematical economics, 18(2):141–153

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.179909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fbef3da6-24d1-403d-a6da-6acbbff49478 · outbound

This paper cites A stochastic subgradient method for distributionally robust non-convex and non-smooth learning.Journal of Optimization Theory and Applications, 194(3):1014–1041.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A stochastic subgradient method for distributionally robust non-convex and non-smooth learning.Journal of Optimization Theory and Applications, 194(3):1014–1041

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.157772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1b4ad295-876a-42f8-ac12-3dbd6512315b · outbound

This paper cites Robust control and model uncertainty.American Economic Review, 91(2):60–66.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust control and model uncertainty.American Economic Review, 91(2):60–66

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.154036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3894da6d-e0e0-46e5-85e0-b8d248f1068a · outbound

This paper cites Uncertainty quantification for plant disease detection using Bayesian deep learning.Applied Soft Computing, 96:106597.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Uncertainty quantification for plant disease detection using Bayesian deep learning.Applied Soft Computing, 96:106597

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.146963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1504d14f-e0a7-46da-91a8-9edee486b7e7 · outbound

This paper cites Model uncertainty, recalibration, and the emer- gence of delta–vega hedging.Finance Stoch., 21:873–930.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Model uncertainty, recalibration, and the emer- gence of delta–vega hedging.Finance Stoch., 21:873–930

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.143277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dbc25685-81d2-4efb-ae05-d51ba700acb7 · outbound

This paper cites Hedging with small uncertainty aversion.Finance Stoch., 21:1–64.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Hedging with small uncertainty aversion.Finance Stoch., 21:1–64

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.139481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 85d6e274-e547-437d-8f1f-bed5cf17509e · outbound

This paper cites an unresolved cited work.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-05-24T02:45:57.131951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d63be46a-a706-4493-bc83-f165210837d6 · outbound

This paper cites Robust risk-aware reinforcement learning.SIAM Journal on Financial Mathematics, 13(1):213–226.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust risk-aware reinforcement learning.SIAM Journal on Financial Mathematics, 13(1):213–226

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.128044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 43146af5-77c8-46e2-bb2e-1943b6a00d4b · outbound

This paper cites Poisoning attacks on data- driven utility learning in games.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Poisoning attacks on data- driven utility learning in games

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.209713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d49acf4d-fd73-437e-93c6-ccb89f841f98 · outbound

This paper cites Improvements on scalable stochastic Bayesian inference methods for multivariate hawkes process.Statistics and Computing, 34(2):85.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Improvements on scalable stochastic Bayesian inference methods for multivariate hawkes process.Statistics and Computing, 34(2):85

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.119943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 882de3f1-a7a3-4911-b8f7-5dfbf3b2ba27 · outbound

This paper cites Sensitivity of causal distributionally robust optimization.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Sensitivity of causal distributionally robust optimization

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.740274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fb6877f9-b9f8-47af-a364-093d939d6842 · outbound

This paper cites Robust reinforcement learning via adversarial training with langevin dynamics.Advances in Neural Information Processing Systems, 33:8127–8138.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust reinforcement learning via adversarial training with langevin dynamics.Advances in Neural Information Processing Systems, 33:8127–8138

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.116471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d34b6287-eb2a-47e7-a3e2-9446bf0d4f46 · outbound

This paper cites an unresolved cited work.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-05-24T02:45:57.112612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5830f574-a23b-4656-bfba-b1363e7a8306 · outbound

This paper cites A smooth model of decision making under ambiguity.Econometrica, 73(6):1849–1892.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A smooth model of decision making under ambiguity.Econometrica, 73(6):1849–1892

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.226308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 109bf726-24c1-49d5-a6b1-7fc6f1ac2373 · outbound

This paper cites Houghton Mifflin.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Houghton Mifflin

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.102472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 831d1a5f-e167-4acd-b3c2-bab1eda63cde · outbound

This paper cites Appointment scheduling under time-dependent patient no-show behavior.Management Science, 66(8):3480–3500.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Appointment scheduling under time-dependent patient no-show behavior.Management Science, 66(8):3480–3500

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.098539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c5250e7-35f5-4128-a0c6-7002f3fda138 · outbound

This paper cites Risk measures based on weak optimal transport.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Risk measures based on weak optimal transport

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.715692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c099bfcf-f0bd-4862-86a5-6eed64303d6c · outbound

This paper cites Principled learn- ing method for Wasserstein distributionally robust optimization with local perturbations.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Principled learn- ing method for Wasserstein distributionally robust optimization with local perturbations

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.095139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 741c1dc5-4453-42bc-90f4-70c9035548b3 · outbound

This paper cites On the adversarial robustness of robust estimators.IEEE Transactions on Information Theory, 66(8):5097–5109.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems On the adversarial robustness of robust estimators.IEEE Transactions on Information Theory, 66(8):5097–5109

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.240772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1904573e-72ab-4f96-9852-91ff4c2a03ef · outbound

This paper cites Bipolar Theorems for Sets of Non-negative Random Variables.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Bipolar Theorems for Sets of Non-negative Random Variables

Reference 75

Resolution: verified exact; local_arxiv, observed 2026-05-24T02:43:47.710562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9ae63a6f-8990-4cf0-9da2-4bda7acba646 · outbound

This paper cites Swing contract pricing: with and without Neural Networks.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Swing contract pricing: with and without Neural Networks

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.705488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9f66112f-3826-44e0-bc5e-7cbb8684ec89 · outbound

This paper cites Preconditioned stochastic gradient Langevin dynamics for deep neural networks.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Preconditioned stochastic gradient Langevin dynamics for deep neural networks

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.087951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 981f2fbe-d8d0-4044-8ca7-5b89ecd8b7de · outbound

This paper cites High-order stochastic gradient thermostats for Bayesian learning of deep models.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems High-order stochastic gradient thermostats for Bayesian learning of deep models

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.084497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b1fa5dd7-7848-4422-89bc-9bb15ddbe553 · outbound

This paper cites Policy gradient algorithms for robust mdps with non-rectangular uncertainty sets.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Policy gradient algorithms for robust mdps with non-rectangular uncertainty sets

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.700333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6aeb351a-c0cd-41cf-9bd8-11ecb0d597c7 · outbound

This paper cites Scalable mcmc for mixed membership stochastic blockmodels.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Scalable mcmc for mixed membership stochastic blockmodels

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.081433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 26ba7677-1724-47c3-8015-8ce9437a82b3 · outbound

This paper cites Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.688619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3192b994-b8e4-4f10-b0da-24f3fa6af5d4 · outbound

This paper cites Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.639612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6cb84953-e660-4a01-aea8-ea6c22a2939c · outbound

This paper cites Non-asymptotic estimates for tusla algorithm for non-convex learning with applications to neural networks with ReLU activation function.IMA Journal of Numerical Analysis.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Non-asymptotic estimates for tusla algorithm for non-convex learning with applications to neural networks with ReLU activation function.IMA Journal of Numerical Analysis

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.078430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 49efc588-6368-4840-af66-d3d160965aea · outbound

This paper cites A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-07-17T01:20:34.521445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 89890732-3452-4025-bdb2-4f13be0da70b · outbound

This paper cites Distributionally robust q-learning.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Distributionally robust q-learning

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.106003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1bccca8d-1827-4a97-8487-c961a9575d85 · outbound

This paper cites Differential Bayesian Neural Nets.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Differential Bayesian Neural Nets

Reference 86

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.683463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cd220db1-f954-4329-96b1-25b2e9ff5dc2 · outbound

This paper cites Taming neural networks with tusla: Nonconvex learning via adaptive stochastic gradient langevin algorithms.SIAM Journal on Mathematics of Data Science, 5(2):323–345.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Taming neural networks with tusla: Nonconvex learning via adaptive stochastic gradient langevin algorithms.SIAM Journal on Mathematics of Data Science, 5(2):323–345

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.071835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c325ec5b-2cc8-467e-991b-a877a71aaaa9 · outbound

This paper cites A complete recipe for stochastic gradient mcmc.Advances in neural information processing systems, 28.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A complete recipe for stochastic gradient mcmc.Advances in neural information processing systems, 28

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.068447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5717bac9-26a0-410f-840c-d589e8036d49 · outbound

This paper cites Ambiguity aversion, robustness, and the variational representation of preferences.Econometrica, 74(6):1447–1498.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Ambiguity aversion, robustness, and the variational representation of preferences.Econometrica, 74(6):1447–1498

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.065332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 19de4941-25ca-4fc5-ba13-61fc2b518dc1 · outbound

This paper cites Appointment scheduling with limited distributional information.Management Science, 61(2):316–334.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Appointment scheduling with limited distributional information.Management Science, 61(2):316–334

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.060130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d69b846b-26ed-489c-a246-fadf22f44053 · outbound

This paper cites Robust utility maximization in nondominated models with 2BSDE: the uncertain volatility model.Mathematical Finance, 25(2):258–287.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust utility maximization in nondominated models with 2BSDE: the uncertain volatility model.Mathematical Finance, 25(2):258–287

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.056666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 042b17fb-b175-4ac5-80db-7036ce6a3c40 · outbound

This paper cites Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations.Mathematical Programming, 171(1-2):115–166.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations.Mathematical Programming, 171(1-2):115–166

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.053233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a1d17774-1cc3-469e-812d-e2cf0b6e84fc · outbound

This paper cites Latent dirichlet analysis of categorical survey responses.Journal of Business & Economic Statistics, 40(1):256–271.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Latent dirichlet analysis of categorical survey responses.Journal of Business & Economic Statistics, 40(1):256–271

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.049687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 41836818-2e90-4b42-96c8-3a0688d0f12f · outbound

This paper cites Stochastic gradient markov chain monte carlo.Journal of the American Statistical Association, 116(533):433–450.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Stochastic gradient markov chain monte carlo.Journal of the American Statistical Association, 116(533):433–450

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.135808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1f394a1a-4ef3-4c75-87b3-785a1f3e2b63 · outbound

This paper cites A parametric approach to the estimation of convex risk functionals based on Wasserstein distance.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A parametric approach to the estimation of convex risk functionals based on Wasserstein distance

Reference 95

Resolution: metadata mismatch; arxiv_id, observed 2026-05-24T02:43:47.670443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 766e0f22-bb44-453b-8ef7-9d0329b01a60 · outbound

This paper cites Superreplication under volatility uncertainty for measurable claims.Electronic Journal of Probability, 18(none):1 – 14.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Superreplication under volatility uncertainty for measurable claims.Electronic Journal of Probability, 18(none):1 – 14

Reference 96

Resolution: verified exact; doi, observed 2026-05-24T02:43:47.333064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 026e2e74-f77e-4c64-8d7e-6b4d07c91a9b · outbound

This paper cites Robust utility maximization with l ´evy processes.Mathematical Finance, 28(1):82–105.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust utility maximization with l ´evy processes.Mathematical Finance, 28(1):82–105

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.046355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cfffa923-9269-4b89-a7d6-bfbffb4efde4 · outbound

This paper cites Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust $Q$-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:43:47.656633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 55a38ff2-fa33-4f08-a07c-1b9e5173862d · outbound

This paper cites A deep learning approach to data-driven model-free pricing and to martingale optimal transport.IEEE Transactions on Information Theory, 69(5):3172–3189.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems A deep learning approach to data-driven model-free pricing and to martingale optimal transport.IEEE Transactions on Information Theory, 69(5):3172–3189

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.043041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f78a3127-643e-4dbd-9e8c-8487eb5e81de · outbound

This paper cites Robust utility maximization in discrete-time markets with friction.

Robust SGLD algorithm for solving non-convex distributionally robust optimisation problems Robust utility maximization in discrete-time markets with friction

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T02:45:57.039614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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