Conditional Noise-Contrastive Estimation of Unnormalised Models

10 June 2018

Papers citing "Conditional Noise-Contrastive Estimation of Unnormalised Models"

35 / 35 papers shown

Title
Disentangling Locality and Entropy in Ranking Distillation Andrew Parry Debasis Ganguly Sean MacAvaney 215 0 0 27 May 2025
Binary Losses for Density Ratio EstimationInternational Conference on Learning Representations (ICLR), 2024 Werner Zellinger 367 1 0 28 Jan 2025
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space Peiyu Yu Dinghuai Zhang Hengzhi He Xiaojian Ma Ruiyao Miao ... Deqian Kong Ruiqi Gao Jianwen Xie Guang Cheng Ying Nian Wu 304 9 0 27 May 2024
On the connection between Noise-Contrastive Estimation and Contrastive Divergence Amanda Olmin Jakob Lindqvist Lennart Svensson Fredrik Lindsten 215 1 0 26 Feb 2024
Classification Diffusion Models: Revitalizing Density Ratio Estimation Shahar Yadin Noam Elata T. Michaeli DiffM 262 2 0 15 Feb 2024
Training Discrete Energy-Based Models with Energy Discrepancy Tobias Schröder Chinmay Pani Yingzhen Li Andrew B. Duncan 198 0 0 14 Jul 2023
Energy Discrepancies: A Score-Independent Loss for Energy-Based ModelsNeural Information Processing Systems (NeurIPS), 2023 Tobias Schröder Chinmay Pani Jen Ning Lim Yingzhen Li Sebastian J. Vollmer Andrew B. Duncan 329 12 0 12 Jul 2023
Learning Unnormalized Statistical Models via Compositional OptimizationInternational Conference on Machine Learning (ICML), 2023 Wei Jiang Jiayu Qin Lingyu Wu Changyou Chen Tianbao Yang Lijun Zhang 324 6 0 13 Jun 2023
A Cookbook of Self-Supervised Learning Randall Balestriero Mark Ibrahim Vlad Sobal Ari S. Morcos Shashank Shekhar ... Pierre Fernandez Amir Bar Hamed Pirsiavash Yann LeCun Micah Goldblum SyDa FedML SSL 399 356 0 24 Apr 2023
Fully Variational Noise-Contrastive EstimationScandinavian Conference on Image Analysis (SCIA), 2023 Christopher Zach BDL DRL 152 2 0 04 Apr 2023
Master's Thesis: Out-of-distribution Detection with Energy-based Models Sven Elflein OODD 151 2 0 28 Jan 2023
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation O. Chehab Alexandre Gramfort Aapo Hyvarinen SSL 216 3 0 23 Jan 2023
Self-Adapting Noise-Contrastive Estimation for Energy-Based Models Na Xu 110 2 0 03 Nov 2022
Gradient-Guided Importance Sampling for Learning Binary Energy-Based ModelsInternational Conference on Learning Representations (ICLR), 2022 Meng Liu Haoran Liu Shuiwang Ji 201 5 0 11 Oct 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 176 9 0 29 Apr 2022
Density Ratio Estimation via Infinitesimal ClassificationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Kristy Choi Chenlin Meng Yang Song Stefano Ermon 335 54 0 22 Nov 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Yao Zhang Jeroen Berrevoets M. Schaar CML 271 6 0 06 Aug 2021
On Out-of-distribution Detection with Energy-based Models Sven Elflein Bertrand Charpentier Daniel Zügner Stephan Günnemann OODD 152 22 0 03 Jul 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni Nouha Dziri Hannes Schulz Geoffrey J. Gordon Philip Bachman Rémi Tachet des Combes SSL 157 33 0 25 Jun 2021
And/or trade-off in artificial neurons: impact on adversarial robustness A. Fontana AAML 172 0 0 15 Feb 2021
Active Slices for Sliced Stein DiscrepancyInternational Conference on Machine Learning (ICML), 2021 Wenbo Gong Kaibo Zhang Yingzhen Li José Miguel Hernández-Lobato 293 8 0 05 Feb 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 332 304 0 09 Jan 2021
Learning Energy-Based Models With Adversarial TrainingEuropean Conference on Computer Vision (ECCV), 2020 Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 363 11 0 11 Dec 2020
Contrastive Divergence Learning is a Time Reversal Adversarial GameInternational Conference on Learning Representations (ICLR), 2020 Omer Yair T. Michaeli GAN 350 7 0 06 Dec 2020
No MCMC for me: Amortized sampling for fast and stable training of energy-based modelsInternational Conference on Learning Representations (ICLR), 2020 Will Grathwohl Jacob Kelly Milad Hashemi Mohammad Norouzi Kevin Swersky David Duvenaud 304 75 0 08 Oct 2020
Sliced Kernelized Stein Discrepancy Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato 290 40 0 30 Jun 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 332 121 0 22 Jun 2020
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICANeural Information Processing Systems (NeurIPS), 2020 Ilyes Khemakhem R. Monti Diederik P. Kingma Aapo Hyvarinen CML 356 130 0 26 Feb 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without SamplingInternational Conference on Machine Learning (ICML), 2020 Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud R. Zemel 217 14 0 13 Feb 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like OneInternational Conference on Learning Representations (ICLR), 2019 Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 442 597 0 06 Dec 2019
Minimum Stein Discrepancy EstimatorsNeural Information Processing Systems (NeurIPS), 2019 Alessandro Barp François‐Xavier Briol Andrew B. Duncan Mark Girolami Lester W. Mackey 259 97 0 19 Jun 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 267 55 0 27 Apr 2019
Autoregressive Energy Machines C. Nash Conor Durkan 106 56 0 11 Apr 2019
General Probabilistic Surface Optimization and Log Density Estimation Dmitry Kopitkov Vadim Indelman 337 1 0 25 Mar 2019
Variational Noise-Contrastive Estimation Benjamin Rhodes Michael U. Gutmann BDL DRL 202 17 0 18 Oct 2018