2 citations · 2 across the 7 of their papers we have counts for
8 papers
Optimality of delayed reward attainment under uncertainty
Chuwei Wang, Alexander Vladimirsky, Anastasia Bizyaeva
Decision making under uncertainty requires balancing the value of additional information against the cost of delaying the decision until that information becomes available. This ch…
Helix-FNO: Spectral-Domain Operator Learning Coupled with a High-Fidelity Mechanistic Model for Fast Surrogate Simulation
Jiabao Zhao, Chuwei Wang, Jinxi Yang
Mechanistic simulation models of full-scale treatment processes remain the only trustworthy, extrapolative description of the underlying physico-chemical dynamics, yet their runtim…
Toward the Thermodynamic Limit: Neural Operators for Non-equilibrium Dynamics of Mott Insulators
Miles Waugh, Chuwei Wang, Radu Andrei +4
Mott insulators exhibit complex photoexcitation dynamics under intense optical driving, with potential implications for carrier multiplication beyond the Shockley-Queisser limit. P…
From Vision to Decision: Neuromorphic Control for Autonomous Navigation and Tracking
Chuwei Wang, Eduardo Sebastián, Amanda Prorok +1
Robotic navigation has historically struggled to reconcile reactive, sensor-based control with the decisive capabilities of model-based planners. This duality becomes critical when…
From Black Hole to Galaxy: Neural Operator: Framework for Accretion and Feedback Dynamics
Nihaal Bhojwani, Chuwei Wang, Hai-Yang Wang +3
Modeling how supermassive black holes co-evolve with their host galaxies is notoriously hard because the relevant physics spans nine orders of magnitude in scale-from milliparsecs…
Physics-Aware Neural Operators for Direct Inversion in 3D Photoacoustic Tomography
Jiayun Wang, Yousuf Aborahama, Arya Khokhar +10
Learning physics-constrained inverse operators-rather than post-processing physics-based reconstructions-is a broadly applicable strategy for problems with expensive forward models…
EquiReg: Equivariance Regularized Diffusion for Inverse Problems
Bahareh Tolooshams, Aditi Chandrashekar, Rayhan Zirvi +4
Diffusion models represent the state-of-the-art for solving inverse problems such as image restoration tasks. Diffusion-based inverse solvers incorporate a likelihood term to guide…
Coarse Graining with Neural Operators for Simulating Chaotic Systems
Chuwei Wang, Boris Bonev, Julius Berner +6
Accurately predicting the long-term behavior of chaotic systems is crucial for various applications such as climate modeling. However, achieving such predictions typically requires…