Search papers, labs, and topics across Lattice.
2
0
3
Forget expensive data generation and unstable PINNs: this method trains neural PDE solvers with cheap, noisy Monte Carlo estimates, achieving up to 8.75x improvement in L2 error.
By recasting the Hamilton-Jacobi-Bellman equation as a tractable Monte Carlo estimation, this work stabilizes physics-informed RL and unlocks its potential for high-dimensional control tasks.
