1 code implementation • 10 Apr 2024 • Yijia Chen, Pinghua Chen, Xiangxin Zhou, Yingtie Lei, Ziyang Zhou, Mingxian Li
Initially, the Texture Mapping Module and Color Perception Adapter collaborate to extract texture and color features from the visible light image.
no code implementations • 25 Mar 2024 • Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang, Quanquan Gu
Antibody design, a crucial task with significant implications across various disciplines such as therapeutics and biology, presents considerable challenges due to its intricate nature.
no code implementations • 7 Mar 2024 • Xiangxin Zhou, Liang Wang, Yichi Zhou
Nevertheless, when applying policy gradients to SDEs, since the policy gradient is estimated on a finite set of trajectories, it can be ill-defined, and the policy behavior in data-scarce regions may be uncontrolled.
no code implementations • 7 Mar 2024 • Yi Xiao, Xiangxin Zhou, Qiang Liu, Liang Wang
In this paper, we present the first systematic survey on multimodal frameworks for molecules research.
no code implementations • 7 Mar 2024 • Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu
DecompOpt presents a new generation paradigm which combines optimization with conditional diffusion models to achieve desired properties while adhering to the molecular grammar.
1 code implementation • 26 Feb 2024 • Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu
Designing 3D ligands within a target binding site is a fundamental task in drug discovery.
1 code implementation • 15 Jan 2024 • Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang
Then the selected protein-ligand subcomplex is processed with SE(3)-equivariant neural networks, and transmitted back to each atom of the complex for augmenting the target-aware 3D molecule diffusion generation with binding interaction information.
no code implementations • 30 Jun 2021 • Yuchi Liu, Zhongdao Wang, Xiangxin Zhou, Liang Zheng
We show that compared with real data, association knowledge obtained from synthetic data can achieve very similar performance on real-world test sets without domain adaption techniques.
4 code implementations • NeurIPS 2019 • Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu
Deep Neural Network (DNN) is powerful but computationally expensive and memory intensive, thus impeding its practical usage on resource-constrained front-end devices.
3 code implementations • 26 Aug 2019 • Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, Gang Yu
This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).
Ranked #5 on 3D Object Detection on nuScenes LiDAR only