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Jen Ning Lim
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2020 – today
- 2023
- [c4]Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew 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 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 Vollmerteke
:
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)
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