The Cabot Professor of Mathematics sat down with Fifteen Minutes to discuss life lessons from mathematics, the challenges of ...
Engineers created multi-layer metalenses that focus several wavelengths. The design could revolutionize portable optical ...
Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, ...
Abstract: Deep neural networks (DNNs) have been applied to address electromagnetic inverse scattering problems (ISPs) and shown superior imaging performances, which can be affected by the training ...
We also prove that the two sets of Maxwell equations only depend on the non-linear elations of the conformal group of ...
We propose a new method called Decoupled Annealing Posterior Sampling (DAPS) that relies on a novel noise annealing process to solve posterior sampling with diffusion prior. Specifically, we decouple ...
Codes for the paper: FlamePINN-1D: Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames. Preprint version: https://arxiv.org ...
What makes the human brain special in the AI era? The answer lies in the way it changes when we start working in ...
Professor Zhou's team provides a rigorous theoretical foundation in their paper. They demonstrate that a specific form of offline Inverse Reinforcement Learning (IRL) reward function can be recovered ...
Physicist Albert Einstein famously posited that if he only had an hour to crack a daunting problem, he'd devote 55 minutes to ...
We’d all like to be innovative, but few people have "creativity switches" they can turn on at will. (I definitely don’t.) ...