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Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models
v1v2 (latest)

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Meng Liu
Haoran Liu
Shuiwang Ji
ArXiv (abs)PDFHTMLGithub (9★)

Papers citing "Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models"

4 / 4 papers shown
Title
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
Sangwoo Shin
H. Hino
87
0
0
02 Aug 2024
Training Discrete Energy-Based Models with Energy Discrepancy
Training Discrete Energy-Based Models with Energy Discrepancy
Tobias Schröder
Zijing Ou
Yingzhen Li
Andrew B. Duncan
56
0
0
14 Jul 2023
Learning Unnormalized Statistical Models via Compositional Optimization
Learning Unnormalized Statistical Models via Compositional Optimization
Wei Jiang
Jiayu Qin
Lingyu Wu
Changyou Chen
Tianbao Yang
Lijun Zhang
105
4
0
13 Jun 2023
Concrete Score Matching: Generalized Score Matching for Discrete Data
Concrete Score Matching: Generalized Score Matching for Discrete Data
Chenlin Meng
Kristy Choi
Jiaming Song
Stefano Ermon
DiffM
262
71
0
02 Nov 2022

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