David Pitt

According to our database, David Pitt authored at least 5 papers between 2004 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition.

Robert Joseph George, David Pitt, Jiawei Zhao, Jean Kossaifi, Cheng Luo, Yuandong Tian, Anima Anandkumar

CoRR, January, 2025

Enabling Automatic Differentiation with Mollified Graph Neural Operators.

Ryan Y. Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel V. Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar

Trans. Mach. Learn. Res., 2025

2024

Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction.

Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar

Trans. Mach. Learn. Res., 2024

A Library for Learning Neural Operators.

Jean Kossaifi, Nikola B. Kovachki, Zongyi Li, David Pitt, Miguel Liu-Schiaffini, Robert Joseph George, Boris Bonev, Kamyar Azizzadenesheli, Julius Berner, Anima Anandkumar

CoRR, 2024

2004

Formalising stories: sequences of events and state changes.

Andrew Vassiliou, Andrew Salway, David Pitt

Proceedings of the 2004 IEEE International Conference on Multimedia and Expo, 2004