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2020 – today
- 2023
[c9]Jiaxin Shi, Ke Alexander Wang, Emily B. Fox:
Sequence Modeling with Multiresolution Convolutional Memory. ICML 2023: 31312-31327- [c8]Ke Alexander Wang, Emily B. Fox:
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. ML4H@NeurIPS 2023: 607-622 - [i10]Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox:
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR abs/2304.14300 (2023) - [i9]Jiaxin Shi, Ke Alexander Wang, Emily B. Fox:
Sequence Modeling with Multiresolution Convolutional Memory. CoRR abs/2305.01638 (2023) - [i8]Ke Alexander Wang, Emily B. Fox:
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. CoRR abs/2312.03344 (2023) - 2022
- [c7]Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque, Tatsunori Hashimoto:
Is Importance Weighting Incompatible with Interpolating Classifiers? ICLR 2022 - 2021
- [c6]Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang:
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. ICBINB@NeurIPS 2021: 80-85 - [c5]Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. ICML 2021: 5279-5289 - [c4]Willie Neiswanger, Ke Alexander Wang, Stefano Ermon:
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information. ICML 2021: 8005-8015 - [i7]Willie Neiswanger, Ke Alexander Wang, Stefano Ermon:
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information. CoRR abs/2104.09460 (2021) - [i6]Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR abs/2106.06695 (2021) - [i5]Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang:
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. CoRR abs/2112.09964 (2021) - [i4]Ke Alexander Wang, Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto:
Is Importance Weighting Incompatible with Interpolating Classifiers? CoRR abs/2112.12986 (2021) - 2020
- [c3]Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. NeurIPS 2020 - [i3]Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson:
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. CoRR abs/2010.13581 (2020)
2010 – 2019
- 2019
- [c2]Ke Alexander Wang, Xinran Bian, Pan Liu
, Donghui Yan:
DC2: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering. IEEE BigData 2019: 5603-5610 - [c1]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. NeurIPS 2019: 14622-14632 - [i2]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. CoRR abs/1903.08114 (2019) - [i1]Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan:
DC2: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering. CoRR abs/1911.06944 (2019)
Coauthor Index
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