Priors in Bayesian Deep Learning: A Review

14 May 2021

Papers citing "Priors in Bayesian Deep Learning: A Review"

50 / 179 papers shown

Title
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 47 209 0 14 May 2020
Prior choice affects ability of Bayesian neural networks to identify unknowns D. Silvestro Tobias Andermann UQCV BDL 37 23 0 11 May 2020
Stable behaviour of infinitely wide deep neural networks Stefano Favaro S. Fortini Stefano Peluchetti BDL 34 28 0 01 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 73 285 0 24 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 48 649 0 20 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 112 487 0 17 Feb 2020
Holes in Bayesian Statistics Andrew Gelman Yuling Yao 19 24 0 15 Feb 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss Vincent Fortuin Martin Josifoski Andreas Krause UQCV 39 127 0 13 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 69 23 0 10 Feb 2020
Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks Beau Coker Melanie F. Pradier Finale Doshi-Velez BDL 16 5 0 12 Dec 2019
Meta-Learning without Memorization Mingzhang Yin George Tucker Mingyuan Zhou Sergey Levine Chelsea Finn VLM 43 186 0 09 Dec 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak Lechao Xiao Jiri Hron Jaehoon Lee Alexander A. Alemi Jascha Narain Sohl-Dickstein S. Schoenholz 50 227 0 05 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 33 23 0 04 Dec 2019
Richer priors for infinitely wide multi-layer perceptrons Russell Tsuchida Fred Roosta M. Gallagher 26 10 0 29 Nov 2019
Function-Space Distributions over Kernels Gregory W. Benton Wesley J. Maddox Jayson Salkey J. Albinati A. Wilson BDL GP 16 26 0 29 Oct 2019
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 53 164 0 29 Oct 2019
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes Greg Yang 78 197 0 28 Oct 2019
Mixture-of-Experts Variational Autoencoder for Clustering and Generating from Similarity-Based Representations on Single Cell Data Andreas Kopf Vincent Fortuin Vignesh Ram Somnath Manfred Claassen DRL 30 12 0 17 Oct 2019
Increasing Expressivity of a Hyperspherical VAE Tim R. Davidson Jakub M. Tomczak E. Gavves 30 6 0 07 Oct 2019
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks Sanjeev Arora S. Du Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang Dingli Yu AAML 47 162 0 03 Oct 2019
Finite Depth and Width Corrections to the Neural Tangent Kernel Boris Hanin Mihai Nica MDE 53 150 0 13 Sep 2019
GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin Dmitry Baranchuk Gunnar Rätsch Stephan Mandt BDL AI4TS 46 247 0 09 Jul 2019
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape Johanni Brea Berfin Simsek Bernd Illing W. Gerstner 72 55 0 05 Jul 2019
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning Sebastian Farquhar Michael A. Osborne Y. Gal UQCV BDL 38 56 0 01 Jul 2019
Quality of Uncertainty Quantification for Bayesian Neural Network Inference Jiayu Yao Weiwei Pan S. Ghosh Finale Doshi-Velez UQCV BDL 118 113 0 24 Jun 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 54 77 0 19 Jun 2019
Large Scale Structure of Neural Network Loss Landscapes Stanislav Fort Stanislaw Jastrzebski 41 83 0 11 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 137 1,677 0 06 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 72 243 0 06 Jun 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 60 124 0 05 Jun 2019
Topological Autoencoders Michael Moor Max Horn Bastian Rieck Karsten Borgwardt 37 149 0 03 Jun 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2 Ali Razavi Aaron van den Oord Oriol Vinyals DRL BDL 105 1,788 0 02 Jun 2019
A Topology Layer for Machine Learning Rickard Brüel-Gabrielsson Bradley J. Nelson Anjan Dwaraknath Primoz Skraba Leonidas Guibas Gunnar Carlsson AI4CE 57 132 0 29 May 2019
On the marginal likelihood and cross-validation Edwin Fong Chris Holmes UQCV 90 110 0 21 May 2019
Output-Constrained Bayesian Neural Networks Wanqian Yang Lars Lorch Moritz Graule Srivatsan Srinivasan Anirudh Suresh Jiayu Yao Melanie F. Pradier Finale Doshi-Velez UQCV BDL 23 12 0 15 May 2019
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions Tim Pearce Russell Tsuchida Mohamed H. Zaki Alexandra Brintrup A. Neely BDL 32 48 0 15 May 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference Hugh Salimbeni Vincent Dutordoir J. Hensman M. Deisenroth BDL 57 43 0 14 May 2019
Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care H. Overweg Anna-Lena Popkes A. Ercole Yingzhen Li José Miguel Hernández-Lobato Yordan Zaykov Cheng Zhang 61 24 0 07 May 2019
Combining Model and Parameter Uncertainty in Bayesian Neural Networks A. Hubin G. Storvik UQCV BDL 37 11 0 18 Mar 2019
Functional Variational Bayesian Neural Networks Shengyang Sun Guodong Zhang Jiaxin Shi Roger C. Grosse BDL 47 236 0 14 Mar 2019
Function Space Particle Optimization for Bayesian Neural Networks Ziyu Wang Tongzheng Ren Jun Zhu Bo Zhang BDL 42 65 0 26 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 146 1,089 0 18 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 118 32 0 15 Feb 2019
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation Greg Yang 92 286 0 13 Feb 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 64 275 0 11 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 80 20 0 07 Feb 2019
Meta-Learning Mean Functions for Gaussian Processes Vincent Fortuin Heiko Strathmann Gunnar Rätsch BDL FedML MLT 51 29 0 23 Jan 2019
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference Xinyu Hu Paul A. Szerlip Theofanis Karaletsos Rohit Singh BDL AI4TS 21 5 0 17 Jan 2019
Attentive Neural Processes Hyunjik Kim A. Mnih Jonathan Richard Schwarz M. Garnelo S. M. Ali Eslami Dan Rosenbaum Oriol Vinyals Yee Whye Teh 77 436 0 17 Jan 2019
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 87 823 0 19 Dec 2018