Kernel Stein Tests for Multiple Model Comparison. - Jen Ning Lim; Makoto Yamada; Bernhard Schölkopf; Wittawat Jitkrittum (NeurIPS, 2019)

More Powerful Selective Kernel Tests for Feature Selection. - Jen Ning Lim; Makoto Yamada; Wittawat Jitkrittum; Yoshikazu Terada; Shigeyuki Matsui; Hidetoshi Shimodaira (AISTATS, 2020)

F-EBM: Energy Based Learning of Functional Data. - Jen Ning Lim; Sebastian J. Vollmer; Lorenz Wolf; Andrew B. Duncan (CoRR, 2022)

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. - Oscar Giles; Kasra Hosseini; Grigorios Mingas; Oliver Strickson; Louise Bowler; Camila Rangel Smith; Harrison Wilde; Jen Ning Lim; Bilal A. Mateen; Kasun Amarasinghe; Rayid Ghani; Alison J. Heppenstall; et al. (CoRR, 2022)

Particle algorithms for maximum likelihood training of latent variable models. - Juan Kuntz; Jen Ning Lim; Adam M. Johansen (AISTATS, 2023)

Energy-Based Models for Functional Data using Path Measure Tilting. - Jen Ning Lim; Sebastian J. Vollmer; Lorenz Wolf; Andrew B. Duncan (AISTATS, 2023)

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. - Tobias Schröder; Zijing Ou; Jen Ning Lim; Yingzhen Li; Sebastian J. Vollmer; Andrew B. Duncan (CoRR, 2023)

Momentum Particle Maximum Likelihood. - Jen Ning Lim; Juan Kuntz; Samuel Power; Adam M. Johansen (ICML, 2024)

Particle Semi-Implicit Variational Inference. - Jen Ning Lim; Adam M. Johansen (NeurIPS, 2024)