Ke Alexander Wang

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 19

Top Topics

Gaussian Process

Top Venues

Publications

Ke Alexander Wang, Emily B. Fox
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. CoRR (2023)
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
Sequence Modeling with Multiresolution Convolutional Memory. CoRR (2023)
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
Sequence Modeling with Multiresolution Convolutional Memory. ICML (2023)
Ke Alexander Wang, Emily B. Fox
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. ML4H@NeurIPS (2023)
Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR (2023)
Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque, Tatsunori Hashimoto
Is Importance Weighting Incompatible with Interpolating Classifiers? ICLR (2022)
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)
Ke Alexander Wang, Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto
Is Importance Weighting Incompatible with Interpolating Classifiers? CoRR (2021)
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information. ICML (2021)
Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. CoRR (2021)
Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. ICBINB@NeurIPS (2021)
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information. CoRR (2021)
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR (2021)
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. NeurIPS (2020)
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints. CoRR (2020)
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)
Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan
: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering. IEEE BigData (2019)
Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan
: A Divide-and-conquer Algorithm for Large-scale Kernel Learning with Application to Clustering. CoRR (2019)
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 (2019)