Andres Potapczynski

26 papers A* 10A 1Journal 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables.
CoRR
Andres Potapczynski, Ravi Kiran Selvam, Tatiana Konstantinova, Shankar Ramasubramanian, Malcolm Wolff, Kin G. Olivares, Ruijun Ma, Mengfei Cao, Michael W. Mahoney, Andrew Gordon Wilson, Boris N. Oreshkin, Dmitry Efimov
2026 J jnl
Zero-shot Forecasting by Simulation Alone.
CoRR
Boris N. Oreshkin, Mayank Jauhari, Ravi Kiran Selvam, Malcolm Wolff, Wenhao Pan, Shankar Ramasubramanian, Kin G. Olivares, Tatiana Konstantinova, Andres Potapczynski, Mengfei Cao, Dmitry Efimov, Michael W. Mahoney, Andrew Gordon Wilson
2025 J jnl
A Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models.
CoRR
Kin G. Olivares, Malcolm Wolff, Tatiana Konstantinova, Shankar Ramasubramanian, Andrew Gordon Wilson, Andres Potapczynski, Willa Potosnak, Mengfei Cao, Boris N. Oreshkin, Dmitry Efimov
2025 A* conf
Customizing the Inductive Biases of Softmax Attention using Structured Matrices.
ICML
Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson
2025 J jnl
Customizing the Inductive Biases of Softmax Attention using Structured Matrices.
CoRR
Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson
2025 A* conf
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra.
ICML
Alan Nawzad Amin, Andres Potapczynski, Andrew Gordon Wilson
2025 J jnl
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra.
CoRR
Alan Nawzad Amin, Andres Potapczynski, Andrew Gordon Wilson
2024 A* conf
Compute Better Spent: Replacing Dense Layers with Structured Matrices.
ICML
Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson
2024 J jnl
Compute Better Spent: Replacing Dense Layers with Structured Matrices.
CoRR
Shikai Qiu, Andres Potapczynski, Marc Finzi, Micah Goldblum, Andrew Gordon Wilson
2024 A* conf
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices.
NeurIPS
Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Charlie Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson
2024 J jnl
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices.
CoRR
Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Zixi Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson
2023 A* conf
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks.
ICLR
Marc Anton Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson
2023 J jnl
A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks.
CoRR
Marc Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson
2023 A* conf
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra.
NeurIPS
Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson
2023 J jnl
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra.
CoRR
Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew Gordon Wilson
2023 A* conf
Simple and Fast Group Robustness by Automatic Feature Reweighting.
ICML
Shikai Qiu, Andres Potapczynski, Pavel Izmailov, Andrew Gordon Wilson
2023 J jnl
Simple and Fast Group Robustness by Automatic Feature Reweighting.
CoRR
Shikai Qiu, Andres Potapczynski, Pavel Izmailov, Andrew Gordon Wilson
2022 J jnl
Low-Precision Arithmetic for Fast Gaussian Processes.
CoRR
Wesley J. Maddox, Andres Potapczynski, Andrew Gordon Wilson
2022 A conf
Low-precision arithmetic for fast Gaussian processes.
UAI
Wesley J. Maddox, Andres Potapczynski, Andrew Gordon Wilson
2022 J jnl
On the Normalizing Constant of the Continuous Categorical Distribution.
CoRR
Elliott Gordon-Rodríguez, Gabriel Loaiza-Ganem, Andres Potapczynski, John P. Cunningham
2022 A* conf
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization.
NeurIPS
Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2022 J jnl
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization.
CoRR
Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2021 A* conf
Bias-Free Scalable Gaussian Processes via Randomized Truncations.
ICML
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
2021 J jnl
Bias-Free Scalable Gaussian Processes via Randomized Truncations.
CoRR
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham
2020 A* conf
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax.
NeurIPS
Andres Potapczynski, Gabriel Loaiza-Ganem, John P. Cunningham
2019 J jnl
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax.
CoRR
Andres Potapczynski, Gabriel Loaiza-Ganem, John P. Cunningham