Bayesian Deep Learning and a Probabilistic Perspective of Generalization

20 February 2020

Papers citing "Bayesian Deep Learning and a Probabilistic Perspective of Generalization"

32 / 32 papers shown

Title
Bayesian Deep Learning for Discrete Choice Daniel F. Villarraga Ricardo A. Daziano BDL AI4CE 64 0 0 23 May 2025
JaxSGMC: Modular stochastic gradient MCMC in JAX Stephan Thaler Paul Fuchs Ana Cukarska Julija Zavadlav BDL 123 2 0 16 May 2025
HopCast: Calibration of Autoregressive Dynamics Models Muhammad Bilal Shahid Cody H. Fleming UQCV 70 0 0 27 Jan 2025
Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images Xiaoge Zhang Tao Wang Chao Yan Fedaa Najdawi Kai Zhou Yuan Ma Yiu-ming Cheung Bradley Malin MedIm 245 0 0 03 Jan 2025
Streamlining Prediction in Bayesian Deep Learning Marcus Klasson Talal Alrawajfeh Mikko Heikkilä Martin Trapp UQCV BDL 133 2 0 27 Nov 2024
pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning Jiahao Lai Jiaqiang Li Jian Xu Yanru Wu Boshi Tang Siqi Chen Yongfeng Huang Wenbo Ding Yang Li FedML 107 0 0 09 Sep 2024
Neural Entropy Akhil Premkumar DiffM 116 0 0 05 Sep 2024
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks Amit Peleg Matthias Hein 43 0 0 04 Jul 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 238 3 0 05 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 90 1 0 31 May 2024
MODL: Multilearner Online Deep Learning Antonios Valkanas Boris N. Oreshkin Mark Coates 85 2 0 28 May 2024
LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention Networks Michelle Halbheer Dominik J. Mühlematter Alexander Becker Dominik Narnhofer Helge Aasen Konrad Schindler Mehmet Özgür Türkoglu UQCV 68 2 0 23 May 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov Hampus Linander UQCV 78 16 0 19 Feb 2024
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets Ossi Raisa Antti Honkela 89 1 0 06 Feb 2024
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks Piyush Tiwary Atri Guha Subhodip Panda Prathosh A.P. MU GAN 75 8 0 25 Sep 2023
Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation Wenbo Hu Xin Sun Qiang liu Wenbo Hu Shu Wu 62 0 0 23 Mar 2023
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 47 50 0 30 Mar 2022
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 61 35 0 17 Mar 2022
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 61 383 0 29 Apr 2021
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 57 315 0 15 Feb 2020
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 69 624 0 05 Dec 2019
Fantastic Generalization Measures and Where to Find Them Yiding Jiang Behnam Neyshabur H. Mobahi Dilip Krishnan Samy Bengio AI4CE 62 599 0 04 Dec 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 54 77 0 19 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
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 74 804 0 07 Feb 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 83 221 0 16 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 172 1,628 0 28 Dec 2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 87 269 0 13 Jun 2018
Essentially No Barriers in Neural Network Energy Landscape Felix Dräxler K. Veschgini M. Salmhofer Fred Hamprecht MoMe 97 430 0 02 Mar 2018
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys Pratik Chaudhari A. Choromańska Stefano Soatto Yann LeCun Carlo Baldassi C. Borgs J. Chayes Levent Sagun R. Zecchina ODL 84 769 0 06 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 355 2,922 0 15 Sep 2016
Expectation Propagation for approximate Bayesian inference T. Minka 104 1,906 0 10 Jan 2013