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Estimating High Order Gradients of the Data Distribution by Denoising
Chenlin Meng, Yang Song, Wenzhe Li +1
The first order derivative of a data density can be estimated efficiently by denoising score matching, and has become an important component in many applications, such as image gen…
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning
Christopher Yeh, Chenlin Meng, Sherrie Wang +7
Progress toward the United Nations Sustainable Development Goals (SDGs) has been hindered by a lack of data on key environmental and socioeconomic indicators, which historically ha…
Pseudo-Spherical Contrastive Divergence
Lantao Yu, Jiaming Song, Yang Song +1
Energy-based models (EBMs) offer flexible distribution parametrization. However, due to the intractable partition function, they are typically trained via contrastive divergence fo…
Equivariant Neural Network for Factor Graphs
Fan-Yun Sun, Jonathan Kuck, Hao Tang +1
Several indices used in a factor graph data structure can be permuted without changing the underlying probability distribution. An algorithm that performs inference on a factor gra…
Multi-Agent Imitation Learning with Copulas
Hongwei Wang, Lantao Yu, Zhangjie Cao +1
Multi-agent imitation learning aims to train multiple agents to perform tasks from demonstrations by learning a mapping between observations and actions, which is essential for und…
Featurized Density Ratio Estimation
Kristy Choi, Madeline Liao, Stefano Ermon
Density ratio estimation serves as an important technique in the unsupervised machine learning toolbox. However, such ratios are difficult to estimate for complex, high-dimensional…