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ORCIDJen Ning Lim
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2020 – today
- 2026
[i8]Agnieszka Dobrowolska, Rogier Hintzen, Martin Balla, Karl Gemayel, Sabine Reichert, Thomas Charman, Jen Ning Lim, Lindsay Edwards, Anna Gogleva:
Tiny Moves: Game-based Hypothesis Refinement. CoRR abs/2602.09801 (2026)- 2024
- [c6]Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen:
Momentum Particle Maximum Likelihood. ICML 2024: 29816-29871 - [c5]Jen Ning Lim, Adam M. Johansen:
Particle Semi-Implicit Variational Inference. NeurIPS 2024 - [i7]Jen Ning Lim, Adam M. Johansen:
Particle Semi-Implicit Variational Inference. CoRR abs/2407.00649 (2024) - 2023
- [c4]Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew B. Duncan:
Energy-Based Models for Functional Data using Path Measure Tilting. AISTATS 2023: 1904-1923 - [c3]Juan Kuntz, Jen Ning Lim, Adam M. Johansen:
Particle algorithms for maximum likelihood training of latent variable models. AISTATS 2023: 5134-5180 - [i6]Tobias Schröder, Zijing Ou, Jen Ning Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew B. Duncan:
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. CoRR abs/2307.06431 (2023) - [i5]Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen:
Momentum Particle Maximum Likelihood. CoRR abs/2312.07335 (2023) - 2022
- [i4]Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew B. Duncan:
F-EBM: Energy Based Learning of Functional Data. CoRR abs/2202.01929 (2022) - [i3]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 J. Vollmer:
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. CoRR abs/2203.01363 (2022) - 2020
- [c2]Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira:
More Powerful Selective Kernel Tests for Feature Selection. AISTATS 2020: 820-830
2010 – 2019
- 2019
- [c1]Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum:
Kernel Stein Tests for Multiple Model Comparison. NeurIPS 2019: 2240-2250 - [i2]Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira:
More Powerful Selective Kernel Tests for Feature Selection. CoRR abs/1910.06134 (2019) - [i1]Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum:
Kernel Stein Tests for Multiple Model Comparison. CoRR abs/1910.12252 (2019)
Coauthor Index
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