3 papers
math.NA2026
Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs
Zakaria Baba, Alexandre M. Bayen, Alexi Canesse +7
We present a neural network-based method for learning scalar hyperbolic conservation laws. Our method replaces the traditional numerical flux in finite volume schemes with a traina…
cs.LG2025
(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs
Nathan Lichtlé, Alexi Canesse, Zhe Fu +3
We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differ…
eess.SY2024
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test
Kathy Jang, Nathan Lichtlé, Eugene Vinitsky +10
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smoot…