A Langevin sampling algorithm inspired by the Adam optimizer | Paper Citation Record

Observation c16da9c4-11fc-43a3-95d2-b7e603529888 · outbound

This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems, 2015.

A Langevin sampling algorithm inspired by the Adam optimizer TensorFlow: Large-scale machine learning on heterogeneous systems, 2015

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.271162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43449a06-0938-4c32-ac39-07b70e8b146e · outbound

This paper cites Adaptive batch sizes for active learning: a probabilistic numerics approach.

A Langevin sampling algorithm inspired by the Adam optimizer Adaptive batch sizes for active learning: a probabilistic numerics approach

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.448191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 600836c6-acfe-4814-a672-b1e27a2d1ead · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.452908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 822d7b43-b0df-45c2-8f21-191e3b165f15 · outbound

This paper cites Benefits of learning rate annealing for tuning-robustness in stochastic optimization.

A Langevin sampling algorithm inspired by the Adam optimizer Benefits of learning rate annealing for tuning-robustness in stochastic optimization

Reference 4

Resolution: verified exact; raw_fallback, observed 2026-08-16T10:15:03.456074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation de321f37-c627-4be8-9180-5ec7a8082a5a · outbound

This paper cites Sampling with time-changed Markov processes.

A Langevin sampling algorithm inspired by the Adam optimizer Sampling with time-changed Markov processes

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.461542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00ebad5-b526-4c66-9f89-eebb126a56b8 · outbound

This paper cites The fundamental incompatibility of scalable Hamiltonian Monte Carlo and naive data subsampling.

A Langevin sampling algorithm inspired by the Adam optimizer The fundamental incompatibility of scalable Hamiltonian Monte Carlo and naive data subsampling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.466499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b9a478-d0d6-4845-a157-d93c5f038c8b · outbound

This paper cites AdamMCMC: combining Metropolis-adjusted Langevin with momentum-based optimization, 2025.

A Langevin sampling algorithm inspired by the Adam optimizer AdamMCMC: combining Metropolis-adjusted Langevin with momentum-based optimization, 2025

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.471905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d72e991-c53e-4f5c-b98b-56de61b0e230 · outbound

This paper cites Covertype.

A Langevin sampling algorithm inspired by the Adam optimizer Covertype

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.477632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 602903e0-d6bd-4b40-bf72-baf46670c484 · outbound

This paper cites Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning.

A Langevin sampling algorithm inspired by the Adam optimizer Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.482579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 561ffee0-0b70-469f-8256-4455fdd60047 · outbound

This paper cites GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo.

A Langevin sampling algorithm inspired by the Adam optimizer GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.488745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 188bcaa2-d938-41c5-8296-01f9e541f2d6 · outbound

This paper cites Long-run accuracy of variational integrators in the stochastic context.

A Langevin sampling algorithm inspired by the Adam optimizer Long-run accuracy of variational integrators in the stochastic context

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.492978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bfb8ddd-7246-46d7-bd19-339f2895a36e · outbound

This paper cites Randomized Hamiltonian Monte Carlo.

A Langevin sampling algorithm inspired by the Adam optimizer Randomized Hamiltonian Monte Carlo

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.496714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a15592d-d69f-4d95-9785-8c972865f7d0 · outbound

This paper cites Handbook of Markov chain Monte Carlo.

A Langevin sampling algorithm inspired by the Adam optimizer Handbook of Markov chain Monte Carlo

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.500410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d590cfa-68ed-43e4-bd38-8e5afb25f862 · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.504257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c258e0dd-113a-4840-8fb9-e2438bfaa6de · outbound

This paper cites Stochastic boundary conditions for molecular dynamics simulations of ST2 water.

A Langevin sampling algorithm inspired by the Adam optimizer Stochastic boundary conditions for molecular dynamics simulations of ST2 water

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.508088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cebf363-4322-4789-a9b0-94a75bffe7ff · outbound

This paper cites Accurate sampling using Langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Accurate sampling using Langevin dynamics

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.511778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2497e3a-a223-4954-9c75-7ebd82e17841 · outbound

This paper cites Cariñena, Eduardo Martínez, and Miguel C.

A Langevin sampling algorithm inspired by the Adam optimizer Cariñena, Eduardo Martínez, and Miguel C

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.515569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cd57754-a694-4b08-bf32-87f327ed8fbc · outbound

This paper cites Statistical practice: Markov chain Monte Carlo in practice.

A Langevin sampling algorithm inspired by the Adam optimizer Statistical practice: Markov chain Monte Carlo in practice

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.519432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 771ff04b-f128-485c-b6b5-39756d7d17ec · outbound

This paper cites Unbiased kinetic Langevin Monte Carlo with inexact gradients.

A Langevin sampling algorithm inspired by the Adam optimizer Unbiased kinetic Langevin Monte Carlo with inexact gradients

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.523236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c20a560-bd0c-4d62-9fee-a5a828c5d092 · outbound

This paper cites Fox, and Carlos Guestrin.

A Langevin sampling algorithm inspired by the Adam optimizer Fox, and Carlos Guestrin

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.528350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b179e430-500f-4a57-baa9-c6826db410c5 · outbound

This paper cites On the convergence of a class of adam-type algorithms for non-convex optimization, 2019.

A Langevin sampling algorithm inspired by the Adam optimizer On the convergence of a class of adam-type algorithms for non-convex optimization, 2019

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.532736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26ba2992-c0fa-4831-8ae6-e34731411a2b · outbound

This paper cites Towards practical PDMP sampling: Metropolis adjustments, locally adaptive step-sizes, and NUTS-based time lengths.

A Langevin sampling algorithm inspired by the Adam optimizer Towards practical PDMP sampling: Metropolis adjustments, locally adaptive step-sizes, and NUTS-based time lengths

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.537137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4432329-36e2-4cde-a47c-6a274e8d47bf · outbound

This paper cites A general system of differential equations to model first-order adaptive algorithms.

A Langevin sampling algorithm inspired by the Adam optimizer A general system of differential equations to model first-order adaptive algorithms

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.541823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be280fe3-ef0d-42da-a1ef-9aabd49cc043 · outbound

This paper cites On sampling from a log-concave density using kinetic langevin diffusions.

A Langevin sampling algorithm inspired by the Adam optimizer On sampling from a log-concave density using kinetic langevin diffusions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.546688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d07e91a-8772-40fa-9f0a-45f054c3683e · outbound

This paper cites Note on learning rate schedules for stochastic optimization.

A Langevin sampling algorithm inspired by the Adam optimizer Note on learning rate schedules for stochastic optimization

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.551333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 113610a8-c927-475d-a0f5-b0a9e60120c9 · outbound

This paper cites Role of molecular dynamics and related methods in drug discovery.

A Langevin sampling algorithm inspired by the Adam optimizer Role of molecular dynamics and related methods in drug discovery

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.555906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e88d0ae-3dd4-45d3-afdd-0bb98c471773 · outbound

This paper cites Optimal linear decay learning rate schedules and further refinements, 2024.

A Langevin sampling algorithm inspired by the Adam optimizer Optimal linear decay learning rate schedules and further refinements, 2024

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.560808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba888e33-b844-4302-929c-2f759b49fc13 · outbound

This paper cites A simple convergence proof of Adam and Adagrad.

A Langevin sampling algorithm inspired by the Adam optimizer A simple convergence proof of Adam and Adagrad

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.566416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 775904cf-d31d-4a11-a7ea-7306fb0ef0d9 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

A Langevin sampling algorithm inspired by the Adam optimizer The mnist database of handwritten digit images for machine learning research

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.571135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c32c2a6b-0fe5-4a20-b80d-003c5b3a2ca1 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding, 2019.

A Langevin sampling algorithm inspired by the Adam optimizer Bert: Pre-training of deep bidirectional transformers for language understanding, 2019

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.574899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 426246b9-c718-415b-a66b-19413b7294ec · outbound

This paper cites Bayesian sam- pling using stochastic gradient thermostats.

A Langevin sampling algorithm inspired by the Adam optimizer Bayesian sam- pling using stochastic gradient thermostats

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.578576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c940ee3-4928-490c-9b19-5d7ab753b1c6 · outbound

This paper cites Incorporating Nesterov Momentum into Adam.

A Langevin sampling algorithm inspired by the Adam optimizer Incorporating Nesterov Momentum into Adam

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.582499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 674189ed-24c0-45a9-b25b-8904c8e42a1a · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.586466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30abee3c-a53f-499f-8bbf-377bb9541e27 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

A Langevin sampling algorithm inspired by the Adam optimizer Adaptive subgradient methods for online learning and stochastic optimization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.590131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ae8b4fa-96d5-43e7-b3a7-2cc07f876d21 · outbound

This paper cites Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:15:03.267003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8092d7f3-cd92-44fe-87d2-8cf29e4533f5 · outbound

This paper cites Peláez, Charlles R.

A Langevin sampling algorithm inspired by the Adam optimizer Peláez, Charlles R

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.598247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97239e07-0284-4d34-8168-1930a869a2c3 · outbound

This paper cites New high-order runge-kutta formulas with step size control for systems of first and second-order differential equations.

A Langevin sampling algorithm inspired by the Adam optimizer New high-order runge-kutta formulas with step size control for systems of first and second-order differential equations

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.601934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 044d7134-fc58-4fb8-a2f1-9ae411f5c2f4 · outbound

This paper cites On the convergence of adaptive approximations for stochastic differential equations.

A Langevin sampling algorithm inspired by the Adam optimizer On the convergence of adaptive approximations for stochastic differential equations

Reference 38

Resolution: verified exact; raw_fallback, observed 2026-08-16T10:15:03.242973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1ccbdbb2-0152-4c2f-9b2d-39e7172c95aa · outbound

This paper cites Riemann manifold langevin and hamiltonian monte carlo methods.

A Langevin sampling algorithm inspired by the Adam optimizer Riemann manifold langevin and hamiltonian monte carlo methods

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.609253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f47e80e7-f6c8-4c12-87de-472d6195b9ce · outbound

This paper cites Velocity jumps for molecular dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Velocity jumps for molecular dynamics

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.612981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc883e66-2c32-4367-aed5-39ce93de3532 · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.617012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1051967c-f0fb-4080-b6f1-15ecd1db4abe · outbound

This paper cites Hopkins, Scott Le Grand, Ross C.

A Langevin sampling algorithm inspired by the Adam optimizer Hopkins, Scott Le Grand, Ross C

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.620555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd794bea-4192-4778-a53a-e1963a5abb74 · outbound

This paper cites Horowitz.

A Langevin sampling algorithm inspired by the Adam optimizer Horowitz

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.624579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50bcb021-266b-492b-b1ee-16f4adcab78b · outbound

This paper cites The adaptive verlet method.

A Langevin sampling algorithm inspired by the Adam optimizer The adaptive verlet method

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.628471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 608b371f-715c-44bb-9709-c8b5089e5442 · outbound

This paper cites Binarized neural networks.

A Langevin sampling algorithm inspired by the Adam optimizer Binarized neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.365100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d31000de-5878-41a2-adc2-2a130fdd40d1 · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.636086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed22500-9caf-442b-9558-d8c04ca0508d · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.640139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4220cf6-785a-4742-8fc3-754ef7c27fc4 · outbound

This paper cites Single-seed generation of Brownian paths and integrals for adaptive and high order SDE solvers.

A Langevin sampling algorithm inspired by the Adam optimizer Single-seed generation of Brownian paths and integrals for adaptive and high order SDE solvers

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.644166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d8c6d22-ad80-401f-a483-38df438fb6f0 · outbound

This paper cites Adaptive stochastic methods for sampling driven molecular systems.

A Langevin sampling algorithm inspired by the Adam optimizer Adaptive stochastic methods for sampling driven molecular systems

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.332816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b25e8029-8baf-4c85-ba34-65f9d20f5745 · outbound

This paper cites Hands-on Bayesian neural networks—a tutorial for deep learning users.

A Langevin sampling algorithm inspired by the Adam optimizer Hands-on Bayesian neural networks—a tutorial for deep learning users

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.319557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 78c38a5b-3d73-4002-8b2a-993dde316bd6 · outbound

This paper cites Higher-order damping mechanisms with applications in optimisation and machine learning.

A Langevin sampling algorithm inspired by the Adam optimizer Higher-order damping mechanisms with applications in optimisation and machine learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.304879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e70a2dd6-71ea-4f15-9b61-55c29aced220 · outbound

This paper cites Analyzing and improving the training dynamics of diffusion models.

A Langevin sampling algorithm inspired by the Adam optimizer Analyzing and improving the training dynamics of diffusion models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.290775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 25cccefd-b0a3-4967-bf44-2c0e3491a169 · outbound

This paper cites A style-based generator architecture for generative adversarial networks, 2019.

A Langevin sampling algorithm inspired by the Adam optimizer A style-based generator architecture for generative adversarial networks, 2019

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.664937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b0ff181-3988-4029-bee0-93c6bd110f35 · outbound

This paper cites Kingma and Jimmy Ba.

A Langevin sampling algorithm inspired by the Adam optimizer Kingma and Jimmy Ba

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.669455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b74f05a-7104-49fc-bce9-919f699507b3 · outbound

This paper cites Computational methods in ordinary differential equations.

A Langevin sampling algorithm inspired by the Adam optimizer Computational methods in ordinary differential equations

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.256450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b5ca6e3b-7ff2-4eba-82cf-79880ee05e9c · outbound

This paper cites Rational construction of stochastic numerical methods for molecular sampling.

A Langevin sampling algorithm inspired by the Adam optimizer Rational construction of stochastic numerical methods for molecular sampling

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.241280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e19820ac-95b6-475d-8999-9f1e2aeefdb5 · outbound

This paper cites Efficient molecular dynamics using geodesic integration and solvent–solute splitting.

A Langevin sampling algorithm inspired by the Adam optimizer Efficient molecular dynamics using geodesic integration and solvent–solute splitting

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.228348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a6ef8470-34db-4862-918a-9f307e380b29 · outbound

This paper cites The computation of averages from equilibrium and nonequilibrium Langevin molecular dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer The computation of averages from equilibrium and nonequilibrium Langevin molecular dynamics

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.215084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7e502444-5572-4861-82f6-aa20fe30028c · outbound

This paper cites Ensemble preconditioning for Markov chain Monte Carlo simulation.

A Langevin sampling algorithm inspired by the Adam optimizer Ensemble preconditioning for Markov chain Monte Carlo simulation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.200419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4656043-a3aa-4e28-bd7d-13c7815e16be · outbound

This paper cites Molecular Dynamics: With Deterministic and Stochastic Numerical Methods.

A Langevin sampling algorithm inspired by the Adam optimizer Molecular Dynamics: With Deterministic and Stochastic Numerical Methods

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.185684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bec2e060-1f7b-4ad3-b65b-210799cdc9fd · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:15:04.171215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 293009fb-a179-473c-93a9-d5a48b63ec7d · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:15:04.157089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a5061662-1c5b-4e21-8f4d-e9a12f3247f5 · outbound

This paper cites How do adam and training strategies help bnns optimization.

A Langevin sampling algorithm inspired by the Adam optimizer How do adam and training strategies help bnns optimization

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.142008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9e7e7263-2c79-4dc8-abb9-f50b78cc2014 · outbound

This paper cites Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise.

A Langevin sampling algorithm inspired by the Adam optimizer Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.128925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8c521396-6745-4578-85a6-180a5a6cfee2 · outbound

This paper cites An Empirical Model of Large-Batch Training.

A Langevin sampling algorithm inspired by the Adam optimizer An Empirical Model of Large-Batch Training

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.717474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10e5138a-2b92-49fa-ac39-2c031d9205ea · outbound

This paper cites Adaptive bound optimization for online convex optimization, 2010.

A Langevin sampling algorithm inspired by the Adam optimizer Adaptive bound optimization for online convex optimization, 2010

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.114064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4809fbae-970b-4f26-927b-62707718ad64 · outbound

This paper cites Design of quasisymplectic propagators for langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Design of quasisymplectic propagators for langevin dynamics

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.098592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6cdd6788-c0ba-4431-a86e-ccc5c581f23a · outbound

This paper cites Rosenbluth, Marshall N.

A Langevin sampling algorithm inspired by the Adam optimizer Rosenbluth, Marshall N

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.083535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84363ede-fa6f-4fa6-9fc8-3174e4bde9b3 · outbound

This paper cites Numerical integration of stochastic differential equations with nonglobally lipschitz coefficients.

A Langevin sampling algorithm inspired by the Adam optimizer Numerical integration of stochastic differential equations with nonglobally lipschitz coefficients

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.068727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 83876ff5-dd89-4cc8-b5ad-f70734f7617a · outbound

This paper cites High-dimensional MCMC with a standard splitting scheme for the underdamped Langevin diffusion.

A Langevin sampling algorithm inspired by the Adam optimizer High-dimensional MCMC with a standard splitting scheme for the underdamped Langevin diffusion

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.054092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b87ec630-aeb6-4af1-be3c-2c0d5a04ce02 · outbound

This paper cites Monnahan, James T.

A Langevin sampling algorithm inspired by the Adam optimizer Monnahan, James T

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.040245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8499b3f1-0a2c-4494-b82d-24f923dfbb1d · outbound

This paper cites Bayesian neural networks, 2018.

A Langevin sampling algorithm inspired by the Adam optimizer Bayesian neural networks, 2018

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:04.026471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 95fa15f9-85b9-4543-bb6b-ce761856c0ce · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:15:04.011585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 41296582-ba34-4798-ac5a-601302a9491e · outbound

This paper cites an unresolved cited work.

A Langevin sampling algorithm inspired by the Adam optimizer Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:15:03.994113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1bc9e479-9e58-4f50-bb8d-8d46e24a4572 · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library.

A Langevin sampling algorithm inspired by the Adam optimizer PyTorch: An imperative style, high-performance deep learning library

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.979480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 56b81ff7-90a3-4952-ab0e-f1fa42db6c38 · outbound

This paper cites Sampling from Bayesian neural network posteriors with symmetric minibatch splitting Langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Sampling from Bayesian neural network posteriors with symmetric minibatch splitting Langevin dynamics

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.964786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1560ef3e-a8de-4537-8eca-20301a93e9fe · outbound

This paper cites Stochastic processes and applications: diffusion processes, the Fokker-Planck and Langevin equations.

A Langevin sampling algorithm inspired by the Adam optimizer Stochastic processes and applications: diffusion processes, the Fokker-Planck and Langevin equations

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.950507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3cb8eef1-a9b6-42a8-83b7-5fabb121d2bf · outbound

This paper cites Numerics with coordinate transforms for efficient Brownian dynamics simulations.

A Langevin sampling algorithm inspired by the Adam optimizer Numerics with coordinate transforms for efficient Brownian dynamics simulations

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.935077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84b7ef6d-c366-4040-bef0-261e089f0aa6 · outbound

This paper cites Unsupervised representation learning with deep convolutional generative adversarial networks, 2016.

A Langevin sampling algorithm inspired by the Adam optimizer Unsupervised representation learning with deep convolutional generative adversarial networks, 2016

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.772475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0caff4c7-393d-4347-a3fc-497d51cf8df2 · outbound

This paper cites Improving language understanding by generative pre-training [openai blog]., 2018.

A Langevin sampling algorithm inspired by the Adam optimizer Improving language understanding by generative pre-training [openai blog]., 2018

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.909778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a0fcef43-2c62-474b-8c3b-d3cfc731edbf · outbound

This paper cites Reddi, Satyen Kale, and Sanjiv Kumar.

A Langevin sampling algorithm inspired by the Adam optimizer Reddi, Satyen Kale, and Sanjiv Kumar

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.780365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20736a53-2459-4478-8c8a-857f5d336034 · outbound

This paper cites Sarhan, and M.

A Langevin sampling algorithm inspired by the Adam optimizer Sarhan, and M

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.885177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c4ee9b66-a47e-489d-9274-08d10b1f7397 · outbound

This paper cites Metropolis adjusted Langevin trajectories: a robust alternative to Hamiltonian Monte Carlo, 2023.

A Langevin sampling algorithm inspired by the Adam optimizer Metropolis adjusted Langevin trajectories: a robust alternative to Hamiltonian Monte Carlo, 2023

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.870813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 791e67fc-ba4b-4521-a7c6-b4c2887e3760 · outbound

This paper cites A Stochastic Approximation Method.

A Langevin sampling algorithm inspired by the Adam optimizer A Stochastic Approximation Method

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.855575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c5adfdda-0dd8-4012-ae2b-536bffbef94b · outbound

This paper cites Optimal scaling of discrete approximations to Langevin diffusions.

A Langevin sampling algorithm inspired by the Adam optimizer Optimal scaling of discrete approximations to Langevin diffusions

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.797235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 342cb840-466f-4f15-b671-ca3ded3b02ac · outbound

This paper cites Roberts and Richard L.

A Langevin sampling algorithm inspired by the Adam optimizer Roberts and Richard L

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.801574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16bba334-0fb2-4c0f-bc10-c2d42662068d · outbound

This paper cites An adaptive discretization algorithm for the weak approximation of stochastic differential equations.

A Langevin sampling algorithm inspired by the Adam optimizer An adaptive discretization algorithm for the weak approximation of stochastic differential equations

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.823198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 20869330-43e2-493a-9765-42a967d25dc3 · outbound

This paper cites Langevin dynamics with variable coefficients and nonconservative forces: from stationary states to numerical methods.

A Langevin sampling algorithm inspired by the Adam optimizer Langevin dynamics with variable coefficients and nonconservative forces: from stationary states to numerical methods

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.809637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b9f5c713-9d98-49f6-88b6-642cafcc128c · outbound

This paper cites Biomolecular dynamics at long timesteps.

A Langevin sampling algorithm inspired by the Adam optimizer Biomolecular dynamics at long timesteps

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.796147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d40ee48f-1914-4785-85f3-b5ae302a3eba · outbound

This paper cites Covariance-controlled adaptive langevin thermostat for large-scale bayesian sampling.

A Langevin sampling algorithm inspired by the Adam optimizer Covariance-controlled adaptive langevin thermostat for large-scale bayesian sampling

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.783718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1b48f3d8-34cd-465a-a9d5-8758f92e4a1c · outbound

This paper cites Random reshuffling for stochastic gradient Langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer Random reshuffling for stochastic gradient Langevin dynamics

Reference 91

Resolution: verified exact; raw_fallback, observed 2026-08-16T10:15:03.093138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 47e9c28c-ce5e-4c84-ad0d-cb2694f26fd5 · outbound

This paper cites Randomised Splitting Methods and Stochastic Gradient Descent.

A Langevin sampling algorithm inspired by the Adam optimizer Randomised Splitting Methods and Stochastic Gradient Descent

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.827928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c3f446-1540-4ea4-8709-80a854ed6f81 · outbound

This paper cites Integration schemes for molecular dynamics and related applications.

A Langevin sampling algorithm inspired by the Adam optimizer Integration schemes for molecular dynamics and related applications

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.770442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 80c37ae4-9bdf-49f0-87fc-444dc94a3ef9 · outbound

This paper cites An impulse integrator for Langevin dynamics.

A Langevin sampling algorithm inspired by the Adam optimizer An impulse integrator for Langevin dynamics

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.756209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 92dd7fa0-90d0-4bc9-a501-d30bfa369ae0 · outbound

This paper cites Don't Decay the Learning Rate, Increase the Batch Size.

A Langevin sampling algorithm inspired by the Adam optimizer Don't Decay the Learning Rate, Increase the Batch Size

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-16T10:15:02.841384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d629361-d8b4-4822-9ddd-331346e07d2c · outbound

This paper cites Variable steps for reversible integration methods.

A Langevin sampling algorithm inspired by the Adam optimizer Variable steps for reversible integration methods

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.742014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9d802ba7-b7c0-4f48-afdb-c8e2a559de4d · outbound

This paper cites Mémoire sur le problème des trois corps.

A Langevin sampling algorithm inspired by the Adam optimizer Mémoire sur le problème des trois corps

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.727455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dd0a885b-d9c2-4f02-be61-177035c05528 · outbound

This paper cites Adaptive weak approximation of stochastic differential equations.

A Langevin sampling algorithm inspired by the Adam optimizer Adaptive weak approximation of stochastic differential equations

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.713116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dbe1d9d5-507b-4439-a070-7684c5b1e73f · outbound

This paper cites Stochastic hamiltonian systems: exponential convergence to the invariant measure, and discretization by the implicit euler scheme.

A Langevin sampling algorithm inspired by the Adam optimizer Stochastic hamiltonian systems: exponential convergence to the invariant measure, and discretization by the implicit euler scheme

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.698223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e719f93f-fed7-42db-ab3a-b322137b5db7 · outbound

This paper cites Lecture 6.5 - rmsprop, coursera: Neural networks for machine learning., 2012.

A Langevin sampling algorithm inspired by the Adam optimizer Lecture 6.5 - rmsprop, coursera: Neural networks for machine learning., 2012

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:15:03.684842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers