Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior | Paper Citation Record

Observation 7e8cfd63-be48-45b4-85ec-1e66d91c24ed · outbound

This paper cites A systematic comparison of bayesian deep learning robustness in diabetic retinopathy tasks.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior A systematic comparison of bayesian deep learning robustness in diabetic retinopathy tasks

Reference 1

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Observation 5b3eb237-b1d8-4ca8-9514-522de8239ff3 · outbound

This paper cites Posterior consistency in linear models under shrinkage priors.Biometrika, 100 (4):1011–1018, 2013.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Posterior consistency in linear models under shrinkage priors.Biometrika, 100 (4):1011–1018, 2013

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:20.920527Z

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This paper cites The horseshoe+ estimator of ultra-sparse signals.Bayesian Analysis, 12(4):1105–1131, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior The horseshoe+ estimator of ultra-sparse signals.Bayesian Analysis, 12(4):1105–1131, 2017

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:20.676985Z

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Observation 5be8963b-1ae3-4fa8-bd16-2e90ed979dac · outbound

This paper cites Dirichlet–laplace priors for optimal shrinkage.Journal of the American Statistical Association, 110(512):1479–1490, 2015.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Dirichlet–laplace priors for optimal shrinkage.Journal of the American Statistical Association, 110(512):1479–1490, 2015

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:20.448501Z

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Observation 8e54322f-d6f8-44f3-b0af-1fcebb9362ea · outbound

This paper cites Graph neural networks with convolutional arma filters.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7):3496–3507, 2021.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Graph neural networks with convolutional arma filters.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7):3496–3507, 2021

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:20.131863Z

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Observation e694ee73-d3ce-423d-b56f-e6f18d0ad18e · outbound

This paper cites Optimal approximation with sparsely connected deep neural networks.SIAM Journal on Mathematics of Data Science, 1(1):8–45, 2019.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Optimal approximation with sparsely connected deep neural networks.SIAM Journal on Mathematics of Data Science, 1(1):8–45, 2019

Reference 6

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Observation 07f81906-c357-436d-9b6c-f6f6793b827e · outbound

This paper cites Triple the gamma—a unifying shrinkage prior for variance and variable selection in sparse state space and tvp models.Econometrics, 8(2):20, 2020.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Triple the gamma—a unifying shrinkage prior for variance and variable selection in sparse state space and tvp models.Econometrics, 8(2):20, 2020

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:19.926528Z

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Observation 119b40fe-36df-411e-97a4-5429f498ff05 · outbound

This paper cites Handling sparsity via the horseshoe.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Handling sparsity via the horseshoe

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:19.694998Z

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Observation 827bf352-720b-4a42-98c6-bc3750a144d6 · outbound

This paper cites Fastgcn: Fast learning with graph convolu-tional networks via impor- tance sampling.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Fastgcn: Fast learning with graph convolu-tional networks via impor- tance sampling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:19.451458Z

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Observation df8b6c7f-7f7f-4d5d-9d29-707565652922 · outbound

This paper cites Stochastic gradient hamiltonian monte carlo.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Stochastic gradient hamiltonian monte carlo

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:19.213076Z

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Observation 6ed898b4-b2a8-4385-aa9b-26480e82a99a · outbound

This paper cites Diffusive gibbs sampling.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Diffusive gibbs sampling

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:18.999402Z

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Observation 6b635f94-7a99-4803-922e-0bf69739dda8 · outbound

This paper cites Learning graph convolutional networks for multi- label recognition and applications.IEEE Transactions on JOURNAL OF LATEX CLASS FILES, VOL.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Learning graph convolutional networks for multi- label recognition and applications.IEEE Transactions on JOURNAL OF LATEX CLASS FILES, VOL

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:18.759679Z

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Observation 20c81972-739b-458c-b5e9-36ae4b9fd1e2 · outbound

This paper cites Efficient and scalable bayesian neural nets with rank-1 factors.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Efficient and scalable bayesian neural nets with rank-1 factors

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:18.510481Z

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Observation 8dec3aeb-bfb7-43ad-b8b6-829e7da8f28c · outbound

This paper cites Radial bayesian neural networks: Beyond discrete support in large-scale bayesian deep learning.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Radial bayesian neural networks: Beyond discrete support in large-scale bayesian deep learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:18.292027Z

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Observation 8b91d567-a155-4e80-9688-d6bebe874130 · outbound

This paper cites Encoding the latent posterior of bayesian neural networks for uncertainty quantification.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Encoding the latent posterior of bayesian neural networks for uncertainty quantification.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:18.100077Z

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Observation 6af9e4b8-f92c-42de-97f4-98501f726e9e · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncer- tainty in deep learning.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Dropout as a bayesian approximation: Representing model uncer- tainty in deep learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:17.861577Z

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Observation bce207ba-2241-47cc-80b8-6c18362641ee · outbound

This paper cites The gr2d2 estimator for the precision matrices.Briefings in Bioinformatics, 23(6):bbac426, 2022.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior The gr2d2 estimator for the precision matrices.Briefings in Bioinformatics, 23(6):bbac426, 2022

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:17.621159Z

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Observation 6400aa56-a10f-4998-b434-ceb7f5aba5d1 · outbound

This paper cites Topology- aware graph pooling networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(12):4512– 4518, 2021.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Topology- aware graph pooling networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(12):4512– 4518, 2021

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:17.409060Z

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Observation 5fb0a1ce-7729-4437-844e-f098d50821b0 · outbound

This paper cites A bayesian approach to recurrence in neural networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(8):2527–2537, 2020.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior A bayesian approach to recurrence in neural networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(8):2527–2537, 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:17.196631Z

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Observation 97c80378-21e4-44d6-9391-1cbd6e9a588d · outbound

This paper cites Model selection in bayesian neural networks via horse- shoe priors.J.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Model selection in bayesian neural networks via horse- shoe priors.J

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:16.975673Z

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Observation 7555a0af-bd38-466c-bf53-1490c9602ce9 · outbound

This paper cites Riemann mani- fold langevin and hamiltonian monte carlo methods.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Riemann mani- fold langevin and hamiltonian monte carlo methods

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:16.813935Z

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Observation 7baf30f7-13bc-4d86-8d6d-cc2ef344a762 · outbound

This paper cites Structured shrink- age priors.Journal of Computational and Graphical Statis- tics, 33(1):1–14, 2024.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Structured shrink- age priors.Journal of Computational and Graphical Statis- tics, 33(1):1–14, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:16.567882Z

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This paper cites Forecasting macroe- conomic data with bayesian vars: Sparse or dense? it depends!International Journal of Forecasting, 2025.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Forecasting macroe- conomic data with bayesian vars: Sparse or dense? it depends!International Journal of Forecasting, 2025

Reference 23

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Observation 6d79c57e-749d-4dc7-af99-d2ef0d6bab73 · outbound

This paper cites Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:16.398921Z

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Observation 4ee5e2cd-30c1-4f2e-b83b-a52280d7ec09 · outbound

This paper cites Stochastic variational inference.Journal of Machine Learning Research, 2013.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Stochastic variational inference.Journal of Machine Learning Research, 2013

Reference 25

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Observation f195ebbf-dd1b-45b4-8156-46f6d0130128 · outbound

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

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Hands-on bayesian neural networks-a tutorial for deep learning users

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:16.016204Z

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Observation fa5cbe1d-4526-4cf5-bde7-00c6e625bfb6 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? Advances in Neural Information Processing Systems, 30, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior What uncertainties do we need in bayesian deep learning for computer vision? Advances in Neural Information Processing Systems, 30, 2017

Reference 27

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Observation 6e45ccad-5ee5-4d83-9d07-97de42bd24c7 · outbound

This paper cites Learning multiple layers of features from tiny images.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Learning multiple layers of features from tiny images

Reference 28

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Observation 8b0f8e7f-4753-4c1e-a750-4d8f04eef6d4 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.Advances in Neural Information Processing Systems, 25, 2012.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Imagenet classification with deep convolutional neural networks.Advances in Neural Information Processing Systems, 25, 2012

Reference 29

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Observation c28cf0d9-f16c-4c9d-910d-b1c54dd7ae5c · outbound

This paper cites Simple and scalable predictive un- certainty estimation using deep ensembles.Advances in Neural Information Processing Systems, 30, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Simple and scalable predictive un- certainty estimation using deep ensembles.Advances in Neural Information Processing Systems, 30, 2017

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:15.795640Z

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Observation 3d974bcd-402f-434b-9a89-416e6f2563e8 · outbound

This paper cites Handwritten digit recognition with a back-propagation network.Advances in Neural Informa- tion Processing Systems, 2, 1989.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Handwritten digit recognition with a back-propagation network.Advances in Neural Informa- tion Processing Systems, 2, 1989

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:15.588412Z

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Observation 22a7a76d-90e2-4b66-bf2c-30f473e0b3c1 · outbound

This paper cites Graphmax for text genera- tion.Journal of Artificial Intelligence Research, 78:823–848, 2023.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Graphmax for text genera- tion.Journal of Artificial Intelligence Research, 78:823–848, 2023

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:15.397389Z

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Observation ab38cab7-491d-4c11-afb9-d0885e36d4c8 · outbound

This paper cites Bayesian compression for deep learning.Advances in Neural Information Processing Systems, 30, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Bayesian compression for deep learning.Advances in Neural Information Processing Systems, 30, 2017

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:15.140199Z

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Observation fa0e45f5-07f1-4e89-ae1f-4ba6fd54d769 · outbound

This paper cites Predictive uncertainty estimation via prior networks.Advances in Neural Information Processing Systems, 31, 2018.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Predictive uncertainty estimation via prior networks.Advances in Neural Information Processing Systems, 31, 2018

Reference 34

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Observation 43d1eac6-d6a4-499f-b4e5-f7da6627b62b · outbound

This paper cites The ridgelet prior: A covariance function ap- proach to prior specification for bayesian neural net- works.Journal of Machine Learning Research, 22(157):1–57, 2021.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior The ridgelet prior: A covariance function ap- proach to prior specification for bayesian neural net- works.Journal of Machine Learning Research, 22(157):1–57, 2021

Reference 35

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Observation 464ad3ea-4d9a-422e-8b38-03dd4c5268a6 · outbound

This paper cites Variational dropout sparsifies deep neural networks.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Variational dropout sparsifies deep neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:14.666735Z

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Observation 9e69fbfd-00ae-4248-b233-cc9570bb6bd3 · outbound

This paper cites Stochastic gradient markov chain monte carlo.Journal of the American Statistical Association, 116(533):433–450, 2021.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Stochastic gradient markov chain monte carlo.Journal of the American Statistical Association, 116(533):433–450, 2021

Reference 37

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Observation 49aaaa97-d2f8-45ba-8f25-9d68aa5caf34 · outbound

This paper cites Sparsity information and regularization in the horseshoe and other shrinkage priors.Electronic Journal of Statistics, 11(2):5018–5051, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Sparsity information and regularization in the horseshoe and other shrinkage priors.Electronic Journal of Statistics, 11(2):5018–5051, 2017

Reference 38

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Observation 93c5d1b8-af4b-4ed0-98d4-3c01f555a4e5 · outbound

This paper cites Posterior concentration for sparse deep learning.Advances in Neural Information Processing Systems, 31, 2018.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Posterior concentration for sparse deep learning.Advances in Neural Information Processing Systems, 31, 2018

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:14.474668Z

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Observation 9c94514e-6872-437c-be6a-cd30ac809d9b · outbound

This paper cites Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:39:09.461668Z

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Observation 86179116-a79b-47ea-bdeb-d4c93433ca30 · outbound

This paper cites Tractable function-space variational infer- ence in bayesian neural networks.Advances in Neural Information Processing Systems, 35:22686–22698, 2022.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Tractable function-space variational infer- ence in bayesian neural networks.Advances in Neural Information Processing Systems, 35:22686–22698, 2022

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:14.236387Z

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Observation c42c1bd9-86bf-4f53-9715-d0506b680ddb · outbound

This paper cites Evidential deep learning to quantify classification uncer- tainty.Advances in Neural Information Processing Systems, 31, 2018.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Evidential deep learning to quantify classification uncer- tainty.Advances in Neural Information Processing Systems, 31, 2018

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:14.035300Z

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Observation ec9629bf-848a-40de-8f9b-68eb714ab875 · outbound

This paper cites A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:06.273575Z

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Observation 4abdf994-e6fc-4063-b75a-e148d717a274 · outbound

This paper cites Understanding measures of uncertainty for adversarial example detection.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Understanding measures of uncertainty for adversarial example detection

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:13.841562Z

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Observation 987476f4-b8d0-4103-acdc-6df9b35829f6 · outbound

This paper cites Generalized Dropout.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Generalized Dropout

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:39:09.170918Z

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Observation 6b4b7b9a-46de-4b18-9dd2-f6842ba89efd · outbound

This paper cites Consistent sparse deep learning: Theory and computation.Journal of the American Statistical Association, 117(540):1981–1995, 2022.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Consistent sparse deep learning: Theory and computation.Journal of the American Statistical Association, 117(540):1981–1995, 2022

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:13.547844Z

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Observation e64b5a9d-77d0-4487-8b8b-0c9a0cda71da · outbound

This paper cites Learning sparse deep neural networks with a spike-and-slab prior.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Learning sparse deep neural networks with a spike-and-slab prior

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:13.319853Z

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Observation d9cb7113-b539-4186-b84c-d6cde543b6d0 · outbound

This paper cites Collapsed variational bounds for bayesian neural networks.Advances in Neural Information Processing Systems, 34:25412–25426, 2021.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Collapsed variational bounds for bayesian neural networks.Advances in Neural Information Processing Systems, 34:25412–25426, 2021

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:13.019338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1bcb5d2a-e8b6-46ea-bc26-04a6945128c8 · outbound

This paper cites All you need is a good functional prior for bayesian deep learning.Journal of Machine Learning Research, 23(74):1–56, 2022.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior All you need is a good functional prior for bayesian deep learning.Journal of Machine Learning Research, 23(74):1–56, 2022

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:12.844135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 243c6c1a-df95-4af1-b884-9ee09c62238c · outbound

This paper cites Graph attention networks.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Graph attention networks

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:12.589632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b9363898-621f-4f8e-8cc0-cd3b71428834 · outbound

This paper cites Sparse bayesian learning for end-to-end eeg decoding.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Sparse bayesian learning for end-to-end eeg decoding

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:12.352819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 689685af-22e1-4802-900a-4f9a7815b626 · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Semi-supervised classification with graph convolutional networks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:12.091390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5281d5d3-48b0-4d18-85fe-ed6209d2c5bb · outbound

This paper cites Bayesian learning via stochastic gradient langevin dynamics.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Bayesian learning via stochastic gradient langevin dynamics

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:11.795804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d57bacd-58d0-467e-80c8-3c72355af63a · outbound

This paper cites Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:11.525812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fc1bddfd-12e3-410c-a970-82fc1ef9be57 · outbound

This paper cites How powerful are graph neural networks? In International Conference on Learning Representations, 2018.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior How powerful are graph neural networks? In International Conference on Learning Representations, 2018

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:07.964161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d5a56ef-e876-4745-ab05-e8257d9fc1fe · outbound

This paper cites Scalable stochastic gradient riemannian langevin dynamics in non-diagonal metrics.Transactions on machine learning research, 2023(8), 2023.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Scalable stochastic gradient riemannian langevin dynamics in non-diagonal metrics.Transactions on machine learning research, 2023(8), 2023

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:11.229249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0f7aa82-c06b-4dc9-889c-9dee066d1bcf · outbound

This paper cites Scalable stochastic gradient riemannian langevin dynamics in non-diagonal metrics.Transactions on Machine Learning Research, 2023.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Scalable stochastic gradient riemannian langevin dynamics in non-diagonal metrics.Transactions on Machine Learning Research, 2023

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:10.933984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 465e5606-08d0-48b4-b0bc-24be19fd859e · outbound

This paper cites Bayesian regression using a prior on the model fit: The r2-d2 shrinkage prior.Journal of the American Statistical Association, pages 1–13, 2020.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Bayesian regression using a prior on the model fit: The r2-d2 shrinkage prior.Journal of the American Statistical Association, pages 1–13, 2020

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:10.656294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9d5deeec-7f32-4d0d-9eb0-c6ce43149a3a · outbound

This paper cites Robust graph representation learning via neural sparsification.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Robust graph representation learning via neural sparsification

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:10.433018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7c9262ca-578f-4a76-9fd5-e9c9ff0b5b2c · outbound

This paper cites an unresolved cited work.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:39:09.969015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a175f70-3a6b-4248-a83d-e33536b6e6fe · outbound

This paper cites log 1 ψjl √ 2π exp (1−µψ jl)2 2ψjlµ !# −E q(ψjl |·) log 1 2 e− 1 2 ψjl =Eq(Y|·).

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior log 1 ψjl √ 2π exp (1−µψ jl)2 2ψjlµ !# −E q(ψjl |·) log 1 2 e− 1 2 ψjl =Eq(Y|·)

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:09.741901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5140cecf-2395-4a84-aa70-85bd18a0d236 · outbound

This paper cites His research focuses on medical image analysis, computer vision, machine learning and AI in healthcare.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior His research focuses on medical image analysis, computer vision, machine learning and AI in healthcare

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:39:10.196477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ed12eeba-254c-455c-b5a2-66d66e12a20a · outbound

This paper cites an unresolved cited work.

Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T14:39:02.271901Z

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Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

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