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2020 – today
- 2024
[c4]Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Deep Stochastic Mechanics. ICML 2024- [i7]Xiao Zhang, Ruoxi Jiang, William Gao, Rebecca Willett, Michael Maire:
Residual Connections Harm Self-Supervised Abstract Feature Learning. CoRR abs/2404.10947 (2024) - [i6]Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Embed and Emulate: Contrastive representations for simulation-based inference. CoRR abs/2409.18402 (2024) - [i5]Xiao Zhang, Ruoxi Jiang, Rebecca Willett, Michael Maire:
Nested Diffusion Models Using Hierarchical Latent Priors. CoRR abs/2412.05984 (2024) - 2023
- [c3]Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett:
Training neural operators to preserve invariant measures of chaotic attractors. NeurIPS 2023 - [i4]Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Deep Stochastic Mechanics. CoRR abs/2305.19685 (2023) - [i3]Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett:
Training neural operators to preserve invariant measures of chaotic attractors. CoRR abs/2306.01187 (2023) - 2022
- [c2]Ruoxi Jiang, Rebecca Willett:
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. NeurIPS 2022 - [i2]Ruoxi Jiang, Rebecca Willett:
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. CoRR abs/2211.01554 (2022) - 2021
- [c1]Yinglun Zhu, Dongruo Zhou
, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak:
Pure Exploration in Kernel and Neural Bandits. NeurIPS 2021: 11618-11630 - [i1]Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert D. Nowak:
Pure Exploration in Kernel and Neural Bandits. CoRR abs/2106.12034 (2021)
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