Jen Ning Lim

According to our database, Jen Ning Lim authored at least 8 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Momentum Particle Maximum Likelihood.

Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen

CoRR, 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

Energy-Based Models for Functional Data using Path Measure Tilting.

Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Particle algorithms for maximum likelihood training of latent variable models.

Juan Kuntz, Jen Ning Lim, Adam M. Johansen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

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, Nik Lomax, Nick Malleson, Martin T. O'Reilly, Sebastian Vollmerteke

CoRR, 2022

F-EBM: Energy Based Learning of Functional Data.

Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan

CoRR, 2022

2020

More Powerful Selective Kernel Tests for Feature Selection.

Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Kernel Stein Tests for Multiple Model Comparison.

Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019