Kanishk Bhatia

PRDP: Progressively Refined Differentiable Physics

The physics solvers employed for neural network training are primarily iterative, and hence, differentiating through them introduces a severe computational burden as iterations grow large. Inspired by works in bilevel optimization, we show that full accuracy of the network is achievable through phys…