no code implementations • 11 Sep 2023 • Chunyong Hu, Hang Zheng, Kun Li, Jianyun Xu, Weibo Mao, Maochun Luo, Lingxuan Wang, Mingxia Chen, Qihao Peng, Kaixuan Liu, Yiru Zhao, Peihan Hao, Minzhe Liu, Kaicheng Yu
Multi-sensor modal fusion has demonstrated strong advantages in 3D object detection tasks.
1 code implementation • 2 Aug 2023 • Tengju Ye, Wei Jing, Chunyong Hu, Shikun Huang, Lingping Gao, Fangzhen Li, Jingke Wang, Ke Guo, Wencong Xiao, Weibo Mao, Hang Zheng, Kun Li, Junbo Chen, Kaicheng Yu
Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving.
1 code implementation • 9 Jul 2023 • Jun Cen, Shiwei Zhang, Yixuan Pei, Kun Li, Hang Zheng, Maochun Luo, Yingya Zhang, Qifeng Chen
In this way, RGB images are not required during inference anymore since the 2D knowledge branch provides 2D information according to the 3D LIDAR input.
no code implementations • 24 Apr 2023 • Zhifeng Gao, Xiaohong Ji, Guojiang Zhao, Hongshuai Wang, Hang Zheng, Guolin Ke, Linfeng Zhang
Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery.
no code implementations • 14 Feb 2023 • Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke
However, to our surprise, we design a simple and cheap algorithm (parameter-free) based on the traditional methods and find it is comparable to or even outperforms deep learning based MCG methods in the widely used GEOM-QM9 and GEOM-Drugs benchmarks.
no code implementations • 14 Feb 2023 • Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke
What's more, they claim to perform better than traditional molecular docking, but the approach of comparison is not fair, since traditional methods are not designed for docking on the whole protein without a given pocket.
no code implementations • 12 Feb 2023 • Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke
Extensive experiment results on pocket-based molecular generation demonstrate that VD-Gen can generate novel 3D molecules to fill the target pocket cavity with high binding affinities, significantly outperforming previous baselines.
1 code implementation • ChemRxiv 2022 • Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke
Uni-Mol is composed of two models with the same SE(3)-equivariant transformer architecture: a molecular pretraining model trained by 209M molecular conformations; a pocket pretraining model trained by 3M candidate protein pocket data.
Ranked #1 on Molecular Property Prediction on MUV