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Black-box Coreset Variational Inference

4 November 2022

Papers citing "Black-box Coreset Variational Inference"

39 / 39 papers shown

Title
Gradient-matching coresets for continual learning Lukas Balles Giovanni Zappella Cédric Archambeau CLL DD 67 2 0 09 Dec 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 117 6 0 01 Oct 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 107 236 0 27 Jul 2021
Deep Learning on a Data Diet: Finding Important Examples Early in Training Mansheej Paul Surya Ganguli Gintare Karolina Dziugaite 125 462 0 15 Jul 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 77 21 0 21 Jun 2021
Online Coreset Selection for Rehearsal-based Continual Learning Jaehong Yoon Divyam Madaan Eunho Yang Sung Ju Hwang CLL 90 145 0 02 Jun 2021
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 162 246 0 30 Oct 2020
Semi-supervised Batch Active Learning via Bilevel Optimization Zalan Borsos Marco Tagliasacchi Andreas Krause 139 23 0 19 Oct 2020
$β$ -Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers Dionysis Manousakas Cecilia Mascolo 45 2 0 31 Aug 2020
Dataset Condensation with Gradient Matching Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 126 503 0 10 Jun 2020
Variational Auto-Regressive Gaussian Processes for Continual Learning Sanyam Kapoor Theofanis Karaletsos T. Bui BDL 65 26 0 09 Jun 2020
Coresets via Bilevel Optimization for Continual Learning and Streaming Zalan Borsos Mojmír Mutný Andreas Krause CLL 87 240 0 06 Jun 2020
Optimizing Millions of Hyperparameters by Implicit Differentiation Jonathan Lorraine Paul Vicol David Duvenaud DD 139 416 0 06 Nov 2019
Soft-Label Dataset Distillation and Text Dataset Distillation Ilia Sucholutsky Matthias Schonlau DD 141 135 0 06 Oct 2019
Generalized Inner Loop Meta-Learning Jaya Kumar Alageshan Brandon Amos A. Verma Phu Mon Htut Artem Molchanov Franziska Meier Douwe Kiela Kyunghyun Cho Soumith Chintala AI4CE 95 160 0 03 Oct 2019
Bayesian Batch Active Learning as Sparse Subset Approximation Robert Pinsler Jonathan Gordon Eric T. Nalisnick José Miguel Hernández-Lobato UQCV 69 132 0 06 Aug 2019
Sparse Variational Inference: Bayesian Coresets from Scratch Trevor Campbell Boyan Beronov 59 38 0 07 Jun 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 75 97 0 12 Mar 2019
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 138 743 0 12 Dec 2018
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 99 297 0 27 Nov 2018
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 158 1,057 0 18 Oct 2018
Importance Weighting and Variational Inference Justin Domke Daniel Sheldon 93 108 0 27 Aug 2018
Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting H. Ritter Aleksandar Botev David Barber BDL CLL 91 334 0 20 May 2018
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent Trevor Campbell Tamara Broderick 90 137 0 05 Feb 2018
Variational Continual Learning Cuong V Nguyen Yingzhen Li T. Bui Richard Turner CLL VLM BDL 116 736 0 29 Oct 2017
Automated Scalable Bayesian Inference via Hilbert Coresets Trevor Campbell Tamara Broderick 88 127 0 13 Oct 2017
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 80 635 0 19 May 2017
Reinterpreting Importance-Weighted Autoencoders Chris Cremer Q. Morris David Duvenaud BDL FAtt 125 94 0 10 Apr 2017
Practical Coreset Constructions for Machine Learning Olivier Bachem Mario Lucic Andreas Krause 72 186 0 19 Mar 2017
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 89 116 0 27 Oct 2016
Coresets for Scalable Bayesian Logistic Regression Jonathan H. Huggins Trevor Campbell Tamara Broderick 72 219 0 20 May 2016
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 94 338 0 07 Nov 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 284 1,246 0 01 Sep 2015
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures Mario Lucic Olivier Bachem Andreas Krause 46 80 0 21 Aug 2015
Gradient-based Hyperparameter Optimization through Reversible Learning D. Maclaurin David Duvenaud Ryan P. Adams DD 239 946 0 11 Feb 2015
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 156 1,168 0 31 Dec 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 277 2,628 0 29 Jun 2012
Super-Samples from Kernel Herding Yutian Chen Max Welling Alex Smola 182 343 0 15 Mar 2012
A Unified Framework for Approximating and Clustering Data Dan Feldman M. Langberg 182 458 0 07 Jun 2011