activity
20192022
most citedA Survey on Edge Computing Systems and Tools

338 citations · 481 across the 17 of their papers we have counts for

collaborators

18 papers

cs.LG202215 cited

Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models

Fan Liu, Hao Liu, Wenzhao Jiang

Machine learning based traffic forecasting models leverage sophisticated spatiotemporal auto-correlations to provide accurate predictions of city-wide traffic states. However, exis…

cond-mat.mtrl-sci202258 cited

Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery

Chenru Duan, Fang Liu, Aditya Nandy +1

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. N…

stat.ML20221 cited

Adaptive Noisy Data Augmentation for Regularized Estimation and Inference in Generalized Linear Models

Yinan Li, Fang Liu

We propose the AdaPtive Noise Augmentation (PANDA) procedure to regularize the estimation and inference of generalized linear models (GLMs). PANDA iteratively optimizes the objecti…

eess.IV2022

Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks

Wei Peng, Li Feng, Guoying Zhao +1

The inherent slow imaging speed of Magnetic Resonance Image (MRI) has spurred the development of various acceleration methods, typically through heuristically undersampling the MRI…

cs.CV202221 cited

Transformers Meet Visual Learning Understanding: A Comprehensive Review

Yuting Yang, Licheng Jiao, Xu Liu +4

Dynamic attention mechanism and global modeling ability make Transformer show strong feature learning ability. In recent years, Transformer has become comparable to CNNs methods in…

eess.AS20226 cited

Self-Supervised Speaker Verification with Simple Siamese Network and Self-Supervised Regularization

Mufan Sang, Haoqi Li, Fang Liu +2

Training speaker-discriminative and robust speaker verification systems without speaker labels is still challenging and worthwhile to explore. In this study, we propose an effectiv…