Weitao Du

According to our database, Weitao Du authored at least 27 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design.

Shengchao Liu, Divin Yan, Weitao Du, Weiyang Liu, Zhuoxinran Li, Hongyu Guo, Christian Borgs, Jennifer T. Chayes, Anima Anandkumar

CoRR, 2024

Sculpting Molecules in 3D: A Flexible Substructure Aware Framework for Text-Oriented Molecular Optimization.

Kaiwei Zhang, Yange Lin, Guangcheng Wu, Yuxiang Ren, Xuecang Zhang, Bo Wang, Xiaoyu Zhang, Weitao Du

CoRR, 2024

A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics.

Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Vignesh C. Bhethanabotla, Nakul Rampal, Omar Yaghi, Christian Borgs, Anima Anandkumar, Hongyu Guo, Jennifer T. Chayes

CoRR, 2024

A quatum inspired neural network for geometric modeling.

Weitao Du, Shengchao Liu, Xuecang Zhang

CoRR, 2024

CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations.

Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang

Proceedings of the Database Systems for Advanced Applications, 2024

2023

Power-law Dynamic arising from machine learning.

Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng

CoRR, 2023

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.

Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A new perspective on building efficient and expressive 3D equivariant graph neural networks.

Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion.

Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.

Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang

Proceedings of the International Conference on Machine Learning, 2023

A Flexible Diffusion Model.

Weitao Du, He Zhang, Tao Yang, Yuanqi Du

Proceedings of the International Conference on Machine Learning, 2023

2022

Structure-based Drug Design with Equivariant Diffusion Models.

Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia

CoRR, 2022

Optimization of the number of paddy field blades by modeling the mass and power consumption of dynamic splashes.

Jinbo Ren, Weitao Du, Dingqiang Peng, Desheng Zou, Yimin Shao, Chris K. Mechefske

Comput. Electron. Agric., 2022

SE(3) Equivariant Graph Neural Networks with Complete Local Frames.

Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

Proceedings of the International Conference on Machine Learning, 2022

Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective.

Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Equivariant vector field network for many-body system modeling.

Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu

CoRR, 2021

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss.

Wei Huang, Yayong Li, Weitao Du, Richard Yi Da Xu, Jie Yin, Ling Chen

CoRR, 2021

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization.

Wei Huang, Weitao Du, Richard Yi Da Xu

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Implicit bias of deep linear networks in the large learning rate phase.

Wei Huang, Weitao Du, Richard Yi Da Xu, Chunrui Liu

CoRR, 2020

Mean Field Theory for Deep Dropout Networks: Digging up Gradient Backpropagation Deeply.

Wei Huang, Richard Yi Da Xu, Weitao Du, Yutian Zeng, Yunce Zhao

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2018

Designing an Easy-to-Deploy Improved DVB-C Set-Top Boxes With a Backward Compatible Square-Root Nyquist Filter.

Ruwu Xiao, Xuan Guo, Qiying Lei, Weitao Du, Yuping Zhao

IEEE Trans. Consumer Electron., 2018

A Design of Two Sub-Stage Square-Root Nyquist Matched Filter.

Ruwu Xiao, Qiying Lei, Xuan Guo, Weitao Du, Yuping Zhao

IEEE Access, 2018

2016

Design of a broadband-intermediate-frequency multi-frequency shortwave signal observation system based on FPGA.

Dewen Qi, Xuan Guo, Weitao Du

Proceedings of the IEEE International Conference on Information and Automation, 2016

2015

Design of digital signal spectrum analyzer based on FPGA.

Dewen Qi, Xuan Guo, Weitao Du

Proceedings of the IEEE International Conference on Information and Automation, 2015

2012

A novel flexible foldable systolic architecture FIR filters generator.

Hang Yin, Weitao Du, Yu Hen Hu, Rui Lv

Proceedings of the IEEE 25th International SOC Conference, 2012

2010

A novel 3780-point FFT.

Xiaogang Yang, Weitao Du, Jingang Yu, Rui Lv, Zhanxin Yang

Proceedings of the IEEE International Conference on Wireless Communications, 2010

An improved feedback cancelling method for on-channel repeater.

Qunchao Feng, Yuanzhi Chen, Weitao Du

Proceedings of the IEEE International Conference on Wireless Communications, 2010