1.6k citations · 7.3k across the 231 of their papers we have counts for
27 papers · 1 filter
Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts
Mostafa Karimi, Di Wu, Zhangyang Wang +1
Predicting compound-protein affinity is critical for accelerating drug discovery. Recent progress made by machine learning focuses on accuracy but leaves much to be desired for int…
Practical Solutions for Machine Learning Safety in Autonomous Vehicles
Sina Mohseni, Mandar Pitale, Vasu Singh +1
Autonomous vehicles rely on machine learning to solve challenging tasks in perception and motion planning. However, automotive software safety standards have not fully evolved to a…
In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label Distillation
Ye Yuan, Wuyang Chen, Yang Yang +1
The comparative losses (typically, triplet loss) are appealing choices for learning person re-identification (ReID) features. However, the triplet loss is computationally much more…
DAVID: Dual-Attentional Video Deblurring
Junru Wu, Xiang Yu, Ding Liu +2
Blind video deblurring restores sharp frames from a blurry sequence without any prior. It is a challenging task because the blur due to camera shake, object movement and defocusing…
Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification
Ye Yuan, Wuyang Chen, Tianlong Chen +4
Many real-world applications, such as city-scale traffic monitoring and control, requires large-scale re-identification. However, previous ReID methods often failed to address two…
Learning to Optimize in Swarms
Yue Cao, Tianlong Chen, Zhangyang Wang +1
Learning to optimize has emerged as a powerful framework for various optimization and machine learning tasks. Current such "meta-optimizers" often learn in the space of continuous…