An improved feedback cancelling method for on-channel repeater. - Qunchao Feng; Yuanzhi Chen; Weitao Du (WCNIS, 2010)

A novel 3780-point FFT. - Xiaogang Yang; Weitao Du; Jingang Yu; Rui Lv; Zhanxin Yang (WCNIS, 2010)

A novel flexible foldable systolic architecture FIR filters generator. - Hang Yin 002; Weitao Du; Yu Hen Hu; Rui Lv (SoCC, 2012)

Design of digital signal spectrum analyzer based on FPGA. - Dewen Qi; Xuan Guo; Weitao Du (ICIA, 2015)

Design of a broadband-intermediate-frequency multi-frequency shortwave signal observation system based on FPGA. - Dewen Qi; Xuan Guo; Weitao Du (ICIA, 2016)

A Design of Two Sub-Stage Square-Root Nyquist Matched Filter. - Ruwu Xiao; Qiying Lei; Xuan Guo; Weitao Du; Yuping Zhao (IEEE Access, 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)

Mean Field Theory for Deep Dropout Networks: Digging up Gradient Backpropagation Deeply. - Wei Huang 034; Richard Yi Da Xu; Weitao Du; Yutian Zeng; Yunce Zhao (ECAI, 2020)

Implicit bias of deep linear networks in the large learning rate phase. - Wei Huang 034; Weitao Du; Richard Yi Da Xu; Chunrui Liu (CoRR, 2020)

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization. - Wei Huang 034; Weitao Du; Richard Yi Da Xu (IJCAI, 2021)

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss. - Wei Huang 034; Yayong Li; Weitao Du; Richard Yi Da Xu; Jie Yin 001; Ling Chen 006 (CoRR, 2021)

Equivariant vector field network for many-body system modeling. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Bin Shao; Tie-Yan Liu (CoRR, 2021)

Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. - Wei Huang 034; Yayong Li; Weitao Du; Richard Y. D. Xu; Jie Yin 001; Ling Chen 006; Miao Zhang (ICLR, 2022)

SE(3) Equivariant Graph Neural Networks with Complete Local Frames. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 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)

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 001; Max Welling; Michael M. Bronstein; Bruno E. Correia (CoRR, 2022)

A Flexible Diffusion Model. - Weitao Du; He Zhang; Tao Yang; Yuanqi Du (ICML, 2023)

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. - Shengchao Liu; Weitao Du; Zhi-Ming Ma; Hongyu Guo; Jian Tang 005 (ICML, 2023)

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. - Weitao Du; Jiujiu Chen; Xuecang Zhang; Zhi-Ming Ma; Shengchao Liu (NeurIPS, 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 (NeurIPS, 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; et al. (NeurIPS, 2023)

Power-law Dynamic arising from machine learning. - Wei Chen 034; Weitao Du; Zhi-Ming Ma; Qi Meng (CoRR, 2023)

CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. - Tianyu Zhang; Yuxiang Ren; Wenzheng Feng; Weitao Du; Xuecang Zhang (DASFAA (6), 2024)

A quatum inspired neural network for geometric modeling. - Weitao Du; Shengchao Liu; Xuecang Zhang (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)

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)

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)

Structure-based drug design with equivariant diffusion models. - Arne Schneuing; Charles Harris; Yuanqi Du; Kieran Didi; Arian Rokkum Jamasb; Ilia Igashov; Weitao Du; Carla P. Gomes; Tom L. Blundell; Pietro Lio; Max Welling; Michael M. Bronstein; et al. (Nat. Comput. Sci., 2024)

GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation. - Shengyin Sun; Wenhao Yu 014; Yuxiang Ren; Weitao Du; Liwei Liu; Xuecang Zhang; Ying Hu; Chen Ma 001 (AAAI, 2025)

AlphaNet: Scaling Up Local Frame-based Atomistic Foundation Model. - Bangchen Yin; Jiaao Wang; Weitao Du; Pengbo Wang; Penghua Ying; Haojun Jia; Zisheng Zhang; Yuanqi Du; Carla P. Gomes; Chenru Duan; Hai Xiao; Graeme Henkelman (CoRR, 2025)

Flow Along the K-Amplitude for Generative Modeling. - Weitao Du; Shuning Chang; Jiasheng Tang; Yu Rong; Fan Wang 019; Shengchao Liu (CoRR, 2025)

Sculpting molecules in text-3D space: a flexible substructure aware framework for text-oriented molecular optimization. - Kaiwei Zhang; Yange Lin; Guangcheng Wu; Yuxiang Ren; Xuecang Zhang; Bo Wang; Xiao-Yu Zhang; Weitao Du (BMC Bioinform., 2025)