most citedMulti-fidelity physics constrained neural networks for dynamical systems

33 citations · 106 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CV20241 cited

FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks

Peiran Wu, Che Liu, Canyu Chen +3

Advancements in Multimodal Large Language Models (MLLMs) have significantly improved medical task performance, such as Visual Question Answering (VQA) and Report Generation (RG). H…

cs.MS2024

TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functions

Sibo Cheng, Jinyang Min, Che Liu +1

Data assimilation techniques are often confronted with challenges handling complex high dimensional physical systems, because high precision simulation in complex high dimensional…

cs.LG20244 cited

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale

Sibo Cheng, Hector Chassagnon, Matthew Kasoar +2

Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emis…

cs.CV2024

Noise2Noise Denoising of CRISM Hyperspectral Data

Robert Platt, Rossella Arcucci, Cédric M. John

Hyperspectral data acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) have allowed for unparalleled mapping of the surface mineralogy of Mars. Due to sens…

cs.LG20247 cited

Explainable Global Wildfire Prediction Models using Graph Neural Networks

Dayou Chen, Sibo Cheng, Jinwei Hu +2

Wildfire prediction has become increasingly crucial due to the escalating impacts of climate change. Traditional CNN-based wildfire prediction models struggle with handling missing…

cs.LG202433 cited

Multi-fidelity physics constrained neural networks for dynamical systems

Hao Zhou, Sibo Cheng, Rossella Arcucci

Physics-constrained neural networks are commonly employed to enhance prediction robustness compared to purely data-driven models, achieved through the inclusion of physical constra…