Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling

12 March 2024

Papers citing "Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling"

41 / 41 papers shown

Title
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv Micah Goldblum Hossein Souri Sanyam Kapoor Chen Zhu Yann LeCun A. Wilson UQCV BDL 118 43 0 20 May 2022
Parallel MCMC Without Embarrassing Failures Daniel Augusto R. M. A. de Souza Diego Mesquita Samuel Kaski Luigi Acerbi 103 11 0 22 Feb 2022
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 122 132 0 14 May 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 79 387 0 29 Apr 2021
Bayesian Neural Network Priors Revisited Vincent Fortuin Adrià Garriga-Alonso Sebastian W. Ober F. Wenzel Gunnar Rätsch Richard Turner Mark van der Wilk Laurence Aitchison BDL UQCV 117 141 0 12 Feb 2021
Neural Bootstrapper Minsuk Shin Hyungjoon Cho Hyun-Seok Min Sungbin Lim UQCV BDL 51 7 0 02 Oct 2020
What is being transferred in transfer learning? Behnam Neyshabur Hanie Sedghi Chiyuan Zhang 122 528 0 26 Aug 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 132 656 0 20 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 84 320 0 15 Feb 2020
Towards Making Deep Transfer Learning Never Hurt Ruosi Wan Haoyi Xiong Xingjian Li Zhanxing Zhu Jun Huan 54 21 0 18 Nov 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 700 24,572 0 26 Jul 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes R. Krishnan Mahesh Subedar Omesh Tickoo BDL 58 47 0 12 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 187 1,706 0 06 Jun 2019
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap Edwin Fong Simon Lyddon Chris Holmes 169 36 0 08 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 109 809 0 07 Feb 2019
Rethinking ImageNet Pre-training Kaiming He Ross B. Girshick Piotr Dollár VLM SSeg 132 1,087 0 21 Nov 2018
Nonparametric learning from Bayesian models with randomized objective functions Simon Lyddon S. Walker C. C. Holmes OOD 94 48 0 29 Jun 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 177 272 0 13 Jun 2018
Neural Network Acceptability Judgments Alex Warstadt Amanpreet Singh Samuel R. Bowman 255 1,413 0 31 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 1.1K 7,201 0 20 Apr 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 145 1,673 0 14 Mar 2018
Explicit Inductive Bias for Transfer Learning with Convolutional Networks Xuhong Li Yves Grandvalet Franck Davoine SSL 91 355 0 05 Feb 2018
Strategies for Conceptual Change in Convolutional Neural Networks M. Grachten Carlos Eduardo Cancino-Chacón 37 10 0 05 Nov 2017
A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets P. Chrabaszcz I. Loshchilov Frank Hutter SSeg OOD 177 649 0 27 Jul 2017
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era Chen Sun Abhinav Shrivastava Saurabh Singh Abhinav Gupta VLM 209 2,407 0 10 Jul 2017
Rethinking Atrous Convolution for Semantic Image Segmentation Liang-Chieh Chen George Papandreou Florian Schroff Hartwig Adam SSeg 234 8,494 0 17 Jun 2017
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 74 635 0 19 May 2017
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning Stefan Elfwing E. Uchibe Kenji Doya 145 1,746 0 10 Feb 2017
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 100 1,094 0 16 Aug 2016
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 176 5,049 0 27 Jun 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 362 8,005 0 23 May 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 469 43,357 0 11 Feb 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,637 0 01 Sep 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 128 913 0 17 Feb 2014
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 153 1,168 0 31 Dec 2013
Asymptotically Exact, Embarrassingly Parallel MCMC Willie Neiswanger Chong-Jun Wang Eric Xing FedML 93 330 0 19 Nov 2013
Describing Textures in the Wild Mircea Cimpoi Subhransu Maji Iasonas Kokkinos S. Mohamed Andrea Vedaldi 3DV 153 2,695 0 14 Nov 2013
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 301 26,223 0 11 Nov 2013
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 693 31,571 0 16 Jan 2013
MCMC using Hamiltonian dynamics Radford M. Neal 305 3,282 0 09 Jun 2012
Frustratingly Easy Domain Adaptation Hal Daumé 128 1,800 0 10 Jul 2009