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cs.LG2025
Noisy PDE Training Requires Bigger PINNs
Sebastien Andre-Sloan, Anirbit Mukherjee, Matthew Colbrook
Physics-Informed Neural Networks (PINNs) are increasingly used to approximate solutions of partial differential equations (PDEs), particularly in high dimensions. In real-world set…
cs.LG2025
Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data
Dibyakanti Kumar, Samyak Jha, Anirbit Mukherjee
In this work, we will establish that the Langevin Monte-Carlo algorithm can learn depth-2 neural nets of any size and for any data and we give non-asymptotic convergence rates for…