24 citations · 33 across the 5 of their papers we have counts for
5 papers
Multi-objective Deep Data Generation with Correlated Property Control
Shiyu Wang, Xiaojie Guo, Xuanyang Lin +11
Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular desig…
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang, Yuanqi Du, Xiaojie Guo +3
Designing and generating new data under targeted properties has been attracting various critical applications such as molecule design, image editing and speech synthesis. Tradition…
Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability
Yafei Wang, Bo Pan, Wei Tu +6
Sample average approximation (SAA), a popular method for tractably solving stochastic optimization problems, enjoys strong asymptotic performance guarantees in settings with indepe…
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
Ke Sun, Yafei Wang, Yi Liu +5
Anderson mixing has been heuristically applied to reinforcement learning (RL) algorithms for accelerating convergence and improving the sampling efficiency of deep RL. Despite its…
An explainable two-dimensional single model deep learning approach for Alzheimer's disease diagnosis and brain atrophy localization
Fan Zhang, Bo Pan, Pengfei Shao +4
Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease progression and the improved…