3 papers
cs.LG2026
Rigorous Error Certification for Neural PDE Solvers: From Empirical Residuals to Solution Guarantees
Amartya Mukherjee, Maxwell Fitzsimmons, David C. Del Rey Fernández +1
Uncertainty quantification for partial differential equations is traditionally grounded in discretization theory, where solution error is controlled via mesh/grid refinement. Physi…
cs.LG2025
Almost Sure Convergence Analysis of Differentially Private Stochastic Gradient Methods
Amartya Mukherjee, Jun Liu
Differentially private stochastic gradient descent (DP-SGD) has become the standard algorithm for training machine learning models with rigorous privacy guarantees. Despite its wid…
cs.LG2025
ADiff4TPP: Asynchronous Diffusion Models for Temporal Point Processes
Amartya Mukherjee, Ruizhi Deng, He Zhao +3
This work introduces a novel approach to modeling temporal point processes using diffusion models with an asynchronous noise schedule. At each step of the diffusion process, the no…