11 citations · 28 across the 11 of their papers we have counts for
7 papers · 1 filter
Two Teachers Better Than One: Hardware-Physics Co-Guided Distributed Scientific Machine Learning
Yuchen Yuan, Junhuan Yang, Hao Wan +4
Scientific machine learning (SciML) is increasingly applied to in-field processing, controlling, and monitoring; however, wide-area sensing, real-time demands, and strict energy an…
A Novel Diffusion Model for Pairwise Geoscience Data Generation with Unbalanced Training Dataset
Junhuan Yang, Yuzhou Zhang, Yi Sheng +2
Recently, the advent of generative AI technologies has made transformational impacts on our daily lives, yet its application in scientific applications remains in its early stages.…
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset
Yi Sheng, Junhuan Yang, Jinyang Li +6
As Artificial Intelligence (AI) increasingly integrates into our daily lives, fairness has emerged as a critical concern, particularly in medical AI, where datasets often reflect i…
A Physics-guided Generative AI Toolkit for Geophysical Monitoring
Junhuan Yang, Hanchen Wang, Yi Sheng +2
Full-waveform inversion (FWI) plays a vital role in geoscience to explore the subsurface. It utilizes the seismic wave to image the subsurface velocity map. As the machine learning…
Muffin: A Framework Toward Multi-Dimension AI Fairness by Uniting Off-the-Shelf Models
Yi Sheng, Junhuan Yang, Lei Yang +3
Model fairness (a.k.a., bias) has become one of the most critical problems in a wide range of AI applications. An unfair model in autonomous driving may cause a traffic accident if…
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Yi Sheng, Junhuan Yang, Yawen Wu +5
Along with the progress of AI democratization, neural networks are being deployed more frequently in edge devices for a wide range of applications. Fairness concerns gradually emer…