Bayesian Pseudo-Coresets via Contrastive Divergence

Bayesian Pseudo-Coresets via Contrastive Divergence

20 March 2023

Papers citing "Bayesian Pseudo-Coresets via Contrastive Divergence"

17 / 17 papers shown

Title
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
Dataset Condensation via Efficient Synthetic-Data Parameterization Jang-Hyun Kim Jinuk Kim Seong Joon Oh Sangdoo Yun Hwanjun Song Joonhyun Jeong Jung-Woo Ha Hyun Oh Song DD 461 167 0 30 May 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 152 381 0 22 Mar 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 158 1,129 0 07 Jul 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 268 689 0 19 Oct 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 63 620 0 14 Jul 2020
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 95 723 0 12 Dec 2018
Dynamic Few-Shot Visual Learning without Forgetting Spyros Gidaris N. Komodakis VLM 38 1,125 0 25 Apr 2018
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent Trevor Campbell Tamara Broderick 57 137 0 05 Feb 2018
Automated Scalable Bayesian Inference via Hilbert Coresets Trevor Campbell Tamara Broderick 54 127 0 13 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 132 8,807 0 25 Aug 2017
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 67 232 0 11 Jul 2016
On Markov chain Monte Carlo methods for tall data Rémi Bardenet Arnaud Doucet Chris Holmes 64 276 0 11 May 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 159 14,831 1 21 Dec 2013
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 51 305 0 27 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 128 4,275 0 18 Nov 2011
A Unified Framework for Approximating and Clustering Data Dan Feldman M. Langberg 115 457 0 07 Jun 2011