Variational Noise-Contrastive Estimation. - Benjamin Rhodes; Michael U. Gutmann (AISTATS, 2019)

Telescoping Density-Ratio Estimation. - Benjamin Rhodes; Kai Xu 016; Michael U. Gutmann (NeurIPS, 2020)

Statistical applications of contrastive learning. - Michael U. Gutmann; Steven Kleinegesse; Benjamin Rhodes (CoRR, 2022)

Enhanced gradient-based MCMC in discrete spaces. - Benjamin Rhodes; Michael U. Gutmann (Trans. Mach. Learn. Res., 2022)

Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data. - Vaidotas Simkus; Benjamin Rhodes; Michael U. Gutmann (J. Mach. Learn. Res., 2023)

Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression. - Akash Srivastava; Seungwook Han; Kai Xu 016; Benjamin Rhodes; Michael U. Gutmann (Trans. Mach. Learn. Res., 2023)

Orb: A Fast, Scalable Neural Network Potential. - Mark Neumann; James Gin; Benjamin Rhodes; Steven Bennett; Zhiyi Li; Hitarth Choubisa; Arthur Hussey; Jonathan Godwin (CoRR, 2024)