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From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models

From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models

Aytunc Sahin
Yatao Bian
J. M. Buhmann
Andreas Krause
ArXiv (abs)PDFHTML

Papers citing "From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models"

5 / 5 papers shown
Title
How Interpretable Are Interpretable Graph Neural Networks?
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen
Yatao Bian
Bo Han
James Cheng
90
7
0
12 Jun 2024
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation
Yue Xiang
Dongyao Zhu
Bowen Lei
Dongkuan Xu
Ruqi Zhang
71
6
0
27 Feb 2023
Learning Neural Set Functions Under the Optimal Subset Oracle
Learning Neural Set Functions Under the Optimal Subset Oracle
Zijing Ou
Tingyang Xu
Qinliang Su
Yingzhen Li
P. Zhao
Yatao Bian
BDL
52
10
0
03 Mar 2022
Randomized Algorithms for Monotone Submodular Function Maximization on the Integer Lattice
Randomized Algorithms for Monotone Submodular Function Maximization on the Integer Lattice
Alberto Schiabel
Vyacheslav Kungurtsev
Jakub Mareˇcek
36
1
0
19 Nov 2021
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
Yatao Bian
Yu Rong
Tingyang Xu
Jiaxiang Wu
Andreas Krause
Junzhou Huang
126
16
0
05 Jun 2021