11 citations · 28 across the 12 of their papers we have counts for
12 papers
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.…
APS-USCT: Ultrasound Computed Tomography on Sparse Data via AI-Physic Synergy
Yi Sheng, Hanchen Wang, Yipei Liu +4
Ultrasound computed tomography (USCT) is a promising technique that achieves superior medical imaging reconstruction resolution by fully leveraging waveform information, outperform…
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…
On-Device Unsupervised Image Segmentation
Junhuan Yang, Yi Sheng, Yuzhou Zhang +2
Along with the breakthrough of convolutional neural networks, learning-based segmentation has emerged in many research works. Most of them are based on supervised learning, requiri…
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…
Automated Architecture Search for Brain-inspired Hyperdimensional Computing
Junhuan Yang, Yi Sheng, Sizhe Zhang +6
This paper represents the first effort to explore an automated architecture search for hyperdimensional computing (HDC), a type of brain-inspired neural network. Currently, HDC des…
Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
Zhiding Liang, Zhepeng Wang, Junhuan Yang +4
In the noisy intermediate-scale quantum (NISQ) era, one of the key questions is how to deal with the high noise level existing in physical quantum bits (qubits). Quantum error corr…
Detecting Gender Bias in Transformer-based Models: A Case Study on BERT
Bingbing Li, Hongwu Peng, Rajat Sainju +7
In this paper, we propose a novel gender bias detection method by utilizing attention map for transformer-based models. We 1) give an intuitive gender bias judgement method by comp…
Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search
Hongwu Peng, Shiyang Chen, Zhepeng Wang +9
Molecular similarity search has been widely used in drug discovery to identify structurally similar compounds from large molecular databases rapidly. With the increasing size of ch…