Bregman divergence as general framework to estimate unnormalized statistical models

14 February 2012

Papers citing "Bregman divergence as general framework to estimate unnormalized statistical models"

44 / 44 papers shown

Title
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 116 0 0 08 May 2025
Learning Energy-Based Models by Self-normalising the Likelihood Hugo Senetaire Paul Jeha Pierre-Alexandre Mattei J. Frellsen 157 1 0 10 Mar 2025
Your copula is a classifier in disguise: classification-based copula density estimation David Huk Mark Steel Ritabrata Dutta 244 0 0 05 Nov 2024
Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances Takafumi Kanamori Kodai Yokoyama Takayuki Kawashima 65 0 0 28 Oct 2024
Identifiability of a statistical model with two latent vectors: Importance of the dimensionality relation and application to graph embedding Hiroaki Sasaki CML 83 0 0 30 May 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 141 3 0 18 Apr 2024
On the connection between Noise-Contrastive Estimation and Contrastive Divergence Amanda Olmin Jakob Lindqvist Lennart Svensson Fredrik Lindsten 95 0 0 26 Feb 2024
Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models Sumeet Singh Stephen Tu Vikas Sindhwani DiffM 145 9 0 11 Sep 2023
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression Akash Srivastava Seung-Jun Han Kai Xu Benjamin Rhodes Michael U. Gutmann 126 11 0 01 May 2023
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States F. Castañeda Haruki Nishimura R. McAllister Koushil Sreenath Adrien Gaidon OffRL 133 18 0 27 Jan 2023
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation O. Chehab Alexandre Gramfort Aapo Hyvarinen SSL 116 3 0 23 Jan 2023
Self-Adapting Noise-Contrastive Estimation for Energy-Based Models Na Xu 66 2 0 03 Nov 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 92 9 0 29 Apr 2022
The Optimal Noise in Noise-Contrastive Learning Is Not What You Think O. Chehab Alexandre Gramfort Aapo Hyvarinen OOD 144 11 0 02 Mar 2022
TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models Tijin Yan Tong Zhou Yufeng Zhan Yuanqing Xia DiffM 82 10 0 20 Dec 2021
Density Ratio Estimation via Infinitesimal Classification Kristy Choi Chenlin Meng Yang Song Stefano Ermon 147 48 0 22 Nov 2021
Variational Inference with Holder Bounds Junya Chen Danni Lu Zidi Xiu Ke Bai Lawrence Carin Chenyang Tao 79 6 0 04 Nov 2021
Pseudo-Spherical Contrastive Divergence Lantao Yu Jiaming Song Yang Song Stefano Ermon 129 7 0 01 Nov 2021
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation Bingbin Liu Elan Rosenfeld Pradeep Ravikumar Andrej Risteski 103 15 0 21 Oct 2021
Random Feature Approximation for Online Nonlinear Graph Topology Identification Rohan T. Money Joshin P. Krishnan B. Beferull-Lozano 64 9 0 19 Oct 2021
Unified Interpretation of Softmax Cross-Entropy and Negative Sampling: With Case Study for Knowledge Graph Embedding Hidetaka Kamigaito Katsuhiko Hayashi 103 12 0 14 Jun 2021
The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization Taiki Miyagawa Akinori F. Ebihara 67 3 0 28 May 2021
The extended Bregman divergence and parametric estimation Sancharee Basak A. Basu 14 6 0 22 Jan 2021
Denoising Score Matching with Random Fourier Features Olga Tsymboi Yermek Kapushev Evgeny Burnaev Ivan Oseledets 85 1 0 13 Jan 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 156 274 0 09 Jan 2021
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer Zidi Xiu Junya Chen Ricardo Henao B. Goldstein Lawrence Carin Chenyang Tao 103 10 0 25 Nov 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 229 104 0 22 Jun 2020
Sliced Score Matching: A Scalable Approach to Density and Score Estimation Yang Song Sahaj Garg Jiaxin Shi Stefano Ermon 247 438 0 17 May 2019
Information criteria for non-normalized models Takeru Matsuda Masatoshi Uehara Aapo Hyvarinen 124 10 0 15 May 2019
General Probabilistic Surface Optimization and Log Density Estimation Dmitry Kopitkov Vadim Indelman 133 1 0 25 Mar 2019
Imputation estimators for unnormalized models with missing data Masatoshi Uehara Takeru Matsuda Jae Kwang Kim 85 7 0 08 Mar 2019
Unified estimation framework for unnormalized models with statistical efficiency Masatoshi Uehara Takafumi Kanamori Takashi Takenouchi Takeru Matsuda 52 2 0 23 Jan 2019
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) Traiko Dinev Michael U. Gutmann 191 27 0 23 Oct 2018
Variational Noise-Contrastive Estimation Benjamin Rhodes Michael U. Gutmann BDL DRL 126 17 0 18 Oct 2018
Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance Masatoshi Uehara Takeru Matsuda F. Komaki 78 14 0 24 Aug 2018
Conditional Noise-Contrastive Estimation of Unnormalised Models Ciwan Ceylan Michael U. Gutmann 106 43 0 10 Jun 2018
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning Akash Srivastava Lazar Valkov Chris Russell Michael U. Gutmann Charles Sutton SyDa GAN 126 694 0 22 May 2017
Boosted Generative Models Aditya Grover Stefano Ermon 134 51 0 27 Feb 2017
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 403 157 0 30 Nov 2016
Generative Adversarial Nets from a Density Ratio Estimation Perspective Masatoshi Uehara Issei Sato Masahiro Suzuki Kotaro Nakayama Y. Matsuo GAN 166 103 0 10 Oct 2016
Graph-based Composite Local Bregman Divergences on Discrete Sample Spaces Takafumi Kanamori Takashi Takenouchi 59 1 0 22 Apr 2016
Simultaneous Estimation of Non-Gaussian Components and their Correlation Structure Hiroaki Sasaki Michael U. Gutmann Hayaru Shouno Aapo Hyvarinen CML 38 3 0 18 Jun 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 303 292 0 14 Jan 2015
The Poisson transform for unnormalised statistical models Simon Barthelmé Nicolas Chopin 35 8 0 11 Jun 2014