Ke Alexander Wang

22 papers A* 6Journal 13Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems.
Trans. Mach. Learn. Res.
Xavier Gonzalez, Estefany Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Leo Kozachkov, Christopher Ré, Scott W. Linderman
2025 J jnl
A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems.
CoRR
Xavier Gonzalez, Estefany Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Christopher Ré, Scott W. Linderman
2025 J jnl
Test-time regression: a unifying framework for designing sequence models with associative memory.
CoRR
Ke Alexander Wang, Jiaxin Shi, Emily B. Fox
2023 — conf
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild.
ML4H@NeurIPS
Ke Alexander Wang, Emily B. Fox
2023 J jnl
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild.
CoRR
Ke Alexander Wang, Emily B. Fox
2023 J jnl
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates.
CoRR
Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox
2023 A* conf
Sequence Modeling with Multiresolution Convolutional Memory.
ICML
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
2023 J jnl
Sequence Modeling with Multiresolution Convolutional Memory.
CoRR
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
2022 A* conf
Is Importance Weighting Incompatible with Interpolating Classifiers?
ICLR
Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque, Tatsunori Hashimoto
2021 A* conf
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information.
ICML
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
2021 J jnl
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information.
CoRR
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
2021 — conf
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics.
ICBINB@NeurIPS
Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
2021 J jnl
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics.
CoRR
Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
2021 J jnl
Is Importance Weighting Incompatible with Interpolating Classifiers?
CoRR
Ke Alexander Wang, Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto
2021 A* conf
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes.
ICML
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2021 J jnl
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes.
CoRR
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2020 A* conf
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints.
NeurIPS
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2020 J jnl
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints.
CoRR
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2019 — conf
DC
IEEE BigData
Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan
2019 J jnl
DC
CoRR
Ke Alexander Wang, Xinran Bian, Pan Liu, Donghui Yan
2019 A* conf
Exact Gaussian Processes on a Million Data Points.
NeurIPS
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson
2019 J jnl
Exact Gaussian Processes on a Million Data Points.
CoRR
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson