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2202.09497
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Gradient Estimation with Discrete Stein Operators
Neural Information Processing Systems (NeurIPS), 2022
19 February 2022
Jiaxin Shi
Yuhao Zhou
Jessica Hwang
Michalis K. Titsias
Lester W. Mackey
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Papers citing
"Gradient Estimation with Discrete Stein Operators"
19 / 19 papers shown
Discrete Neural Flow Samplers with Locally Equivariant Transformer
Chinmay Pani
Ruixiang Zhang
Yingzhen Li
479
10
0
23 May 2025
Secrets of GFlowNets' Learning Behavior: A Theoretical Study
Tianshu Yu
183
1
0
04 May 2025
Learning-Order Autoregressive Models with Application to Molecular Graph Generation
Zhe Wang
Jiaxin Shi
N. Heess
Arthur Gretton
Michalis K. Titsias
406
18
0
07 Mar 2025
Simplified and Generalized Masked Diffusion for Discrete Data
Neural Information Processing Systems (NeurIPS), 2024
Jiaxin Shi
Kehang Han
Zehao Wang
Arnaud Doucet
Michalis K. Titsias
DiffM
759
421
0
17 Jan 2025
On Divergence Measures for Training GFlowNets
Neural Information Processing Systems (NeurIPS), 2024
Tiago da Silva
Eliezer de Souza da Silva
Diego Mesquita
BDL
505
5
0
12 Oct 2024
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao
Jiaxin Shi
F. Chen
Shaul Druckmann
Lester W. Mackey
Scott W. Linderman
810
44
0
30 Jul 2024
Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model
Longrong Yang
Dong Shen
Chaoxiang Cai
Fan Yang
Size Li
Tingting Gao
Xi Li
MoE
505
9
0
28 Jun 2024
Adaptive Instrument Design for Indirect Experiments
International Conference on Learning Representations (ICLR), 2023
Yash Chandak
Shiv Shankar
Vasilis Syrgkanis
Emma Brunskill
252
5
0
05 Dec 2023
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick
Neural Information Processing Systems (NeurIPS), 2023
Lennert De Smet
Emanuele Sansone
Pedro Zuidberg Dos Martires
239
15
0
21 Nov 2023
Sparse Backpropagation for MoE Training
Liyuan Liu
Jianfeng Gao
Weizhu Chen
MoE
231
15
0
01 Oct 2023
DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation
Pau Mulet Arabí
Alec Flowers
Lukas Mauch
Fabien Cardinaux
BDL
237
0
0
07 Sep 2023
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality
Neural Information Processing Systems (NeurIPS), 2023
Jose H. Blanchet
Haoxuan Chen
Yiping Lu
Lexing Ying
262
6
0
25 May 2023
Bayesian Numerical Integration with Neural Networks
Katharina Ott
Michael Tiemann
Philipp Hennig
F. Briol
BDL
340
5
0
22 May 2023
Bridging Discrete and Backpropagation: Straight-Through and Beyond
Neural Information Processing Systems (NeurIPS), 2023
Liyuan Liu
Chengyu Dong
Xiaodong Liu
Bin Yu
Jianfeng Gao
BDL
338
38
0
17 Apr 2023
Meta-learning Control Variates: Variance Reduction with Limited Data
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Z. Sun
Chris J. Oates
F. Briol
BDL
376
13
0
08 Mar 2023
A kernel Stein test of goodness of fit for sequential models
International Conference on Machine Learning (ICML), 2022
Jerome Baum
Heishiro Kanagawa
Arthur Gretton
524
12
0
19 Oct 2022
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping
AAAI Conference on Artificial Intelligence (AAAI), 2022
Russell Z. Kunes
Mingzhang Yin
Max Land
Doron Haviv
Dana Peér
Simon Tavaré
BDL
290
5
0
12 Aug 2022
Generalised Bayesian Inference for Discrete Intractable Likelihood
Journal of the American Statistical Association (JASA), 2022
Takuo Matsubara
Jeremias Knoblauch
F. Briol
Chris J. Oates
421
26
0
16 Jun 2022
A Kernel Stein Test for Comparing Latent Variable Models
Heishiro Kanagawa
Wittawat Jitkrittum
Lester W. Mackey
Kenji Fukumizu
Arthur Gretton
516
20
0
01 Jul 2019
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