23 citations · 40 across the 10 of their papers we have counts for
4 papers · 1 filter
Reframing Generative Models for Physical Systems using Stochastic Interpolants
Anthony Zhou, Alexander Wikner, Amaury Lancelin +2
Generative models have recently emerged as powerful surrogates for physical systems, demonstrating increased accuracy, stability, and/or statistical fidelity. Most approaches rely…
BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction
Reid Graves, Anthony Zhou, Amir Barati Farimani
Accurate prediction of blast pressure fields is essential for applications in structural safety, defense planning, and hazard mitigation. Traditional methods such as empirical mode…
Hamiltonian Neural PDE Solvers through Functional Approximation
Anthony Zhou, Amir Barati Farimani
Designing neural networks within a Hamiltonian framework offers a principled way to ensure that conservation laws are respected in physical systems. While promising, these capabili…
Generative Latent Neural PDE Solver using Flow Matching
Zijie Li, Anthony Zhou, Amir Barati Farimani
Autoregressive next-step prediction models have become the de-facto standard for building data-driven neural solvers to forecast time-dependent partial differential equations (PDEs…