no code implementations • 19 Sep 2022 • Zehao Dong, Heming Zhang, Yixin Chen, Philip R. O. Payne, Fuhai Li
Synergistic drug combinations provide huge potentials to enhance therapeutic efficacy and to reduce adverse reactions.
no code implementations • 1 Jul 2022 • Wenjia Zhang, Haoran Xu, Haoyi Niu, Peng Cheng, Ming Li, Heming Zhang, Guyue Zhou, Xianyuan Zhan
In this paper, we propose the Discriminator-guided Model-based offline Imitation Learning (DMIL) framework, which introduces a discriminator to simultaneously distinguish the dynamics correctness and suboptimality of model rollout data against real expert demonstrations.
no code implementations • 14 May 2021 • Zehao Dong, Heming Zhang, Yixin Chen, Fuhai Li
Though deep learning algorithms are widely used in the drug synergy prediction problem, it is still an open problem to formulate the prediction model with biological meaning to investigate the mysterious mechanisms of synergy (MoS) for the human-AI collaboration in healthcare systems.
2 code implementations • ECCV 2020 • Xuewen Yang, Heming Zhang, Di Jin, Yingru Liu, Chi-Hao Wu, Jianchao Tan, Dongliang Xie, Jue Wang, Xin Wang
The goal of this work is to develop a novel learning framework for accurate and expressive fashion captioning.
no code implementations • 5 Jul 2020 • Heming Zhang, Xuewen Yang, Jianchao Tan, Chi-Hao Wu, Jue Wang, C. -C. Jay Kuo
Color compatibility is important for evaluating the compatibility of a fashion outfit, yet it was neglected in previous studies.
no code implementations • 15 May 2019 • Heming Zhang, Xiaolong Wang, C. -C. Jay Kuo
Kinship verification aims to identify the kin relation between two given face images.
no code implementations • 27 Apr 2019 • Heming Zhang, Xiaolong Wang, Jingwen Zhu, C. -C. Jay Kuo
In this work, we present a proposal generation acceleration framework for real-time face detection.
no code implementations • 20 Mar 2019 • Jie Zhang, Junting Zhang, Shalini Ghosh, Dawei Li, Jingwen Zhu, Heming Zhang, Yalin Wang
Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community.
2 code implementations • 19 Mar 2019 • Junting Zhang, Jie Zhang, Shalini Ghosh, Dawei Li, Serafettin Tasci, Larry Heck, Heming Zhang, C. -C. Jay Kuo
The idea is to first train a separate model only for the new classes, and then combine the two individual models trained on data of two distinct set of classes (old classes and new classes) via a novel double distillation training objective.
no code implementations • 26 Feb 2019 • Heming Zhang, Shalini Ghosh, Larry Heck, Stephen Walsh, Junting Zhang, Jie Zhang, C. -C. Jay Kuo
The key challenge of generative Visual Dialogue (VD) systems is to respond to human queries with informative answers in natural and contiguous conversation flow.