127 citations · 278 across the 14 of their papers we have counts for
22 papers · 1 filter
Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song +2
While autoregressive models excel at image compression, their sample quality is often lacking. Although not realistic, generated images often have high likelihood according to the…
Autoregressive Score Matching
Chenlin Meng, Lantao Yu, Yang Song +2
Autoregressive models use chain rule to define a joint probability distribution as a product of conditionals. These conditionals need to be normalized, imposing constraints on the…
Imitation with Neural Density Models
Kuno Kim, Akshat Jindal, Yang Song +3
We propose a new framework for Imitation Learning (IL) via density estimation of the expert's occupancy measure followed by Maximum Occupancy Entropy Reinforcement Learning (RL) us…
Privacy Preserving Recalibration under Domain Shift
Rachel Luo, Shengjia Zhao, Jiaming Song +3
Classifiers deployed in high-stakes real-world applications must output calibrated confidence scores, i.e. their predicted probabilities should reflect empirical frequencies. Recal…
Multi-label Contrastive Predictive Coding
Jiaming Song, Stefano Ermon
Variational mutual information (MI) estimators are widely used in unsupervised representation learning methods such as contrastive predictive coding (CPC). A lower bound on MI can…
Belief Propagation Neural Networks
Jonathan Kuck, Shuvam Chakraborty, Hao Tang +4
Learned neural solvers have successfully been used to solve combinatorial optimization and decision problems. More general counting variants of these problems, however, are still l…