37 citations · 261 across the 37 of their papers we have counts for
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Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions
Huangjie Zheng, Mingyuan Zhou
To measure the difference between two probability distributions, referred to as the source and target, respectively, we exploit both the chain rule and Bayes' theorem to construct…
Bayesian Attention Modules
Xinjie Fan, Shujian Zhang, Bo Chen +1
Attention modules, as simple and effective tools, have not only enabled deep neural networks to achieve state-of-the-art results in many domains, but also enhanced their interpreta…
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition
Dandan Guo, Bo Chen, Wenchao Chen +3
We develop a recurrent gamma belief network (rGBN) for radar automatic target recognition (RATR) based on high-resolution range profile (HRRP), which characterizes the temporal dep…
Mutual Information Gradient Estimation for Representation Learning
Liangjian Wen, Yiji Zhou, Lirong He +2
Mutual Information (MI) plays an important role in representation learning. However, MI is unfortunately intractable in continuous and high-dimensional settings. Recent advances es…
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation
Xinjie Fan, Yizhe Zhang, Zhendong Wang +1
Sequence generation models are commonly refined with reinforcement learning over user-defined metrics. However, high gradient variance hinders the practical use of this method. To…
Poisson-Randomized Gamma Dynamical Systems
Aaron Schein, Scott W. Linderman, Mingyuan Zhou +2
This paper presents the Poisson-randomized gamma dynamical system (PRGDS), a model for sequentially observed count tensors that encodes a strong inductive bias toward sparsity and…