Weitao Du

According to our database1, Weitao Du authored at least 25 papers between 2010 and 2024.

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Bibliography

2024
Sculpting Molecules in 3D: A Flexible Substructure Aware Framework for Text-Oriented Molecular Optimization.
CoRR, 2024

A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics.
CoRR, 2024

A quatum inspired neural network for geometric modeling.
CoRR, 2024

2023
Power-law Dynamic arising from machine learning.
CoRR, 2023

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

A Flexible Diffusion Model.
Proceedings of the International Conference on Machine Learning, 2023

2022
Structure-based Drug Design with Equivariant Diffusion Models.
CoRR, 2022

Optimization of the number of paddy field blades by modeling the mass and power consumption of dynamic splashes.
Comput. Electron. Agric., 2022

SE(3) Equivariant Graph Neural Networks with Complete Local Frames.
Proceedings of the International Conference on Machine Learning, 2022

Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Equivariant vector field network for many-body system modeling.
CoRR, 2021

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss.
CoRR, 2021

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Implicit bias of deep linear networks in the large learning rate phase.
CoRR, 2020

Mean Field Theory for Deep Dropout Networks: Digging up Gradient Backpropagation Deeply.
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.
IEEE Trans. Consumer Electron., 2018

A Design of Two Sub-Stage Square-Root Nyquist Matched Filter.
IEEE Access, 2018

2016
Design of a broadband-intermediate-frequency multi-frequency shortwave signal observation system based on FPGA.
Proceedings of the IEEE International Conference on Information and Automation, 2016

2015
Design of digital signal spectrum analyzer based on FPGA.
Proceedings of the IEEE International Conference on Information and Automation, 2015

2012
A novel flexible foldable systolic architecture FIR filters generator.
Proceedings of the IEEE 25th International SOC Conference, 2012

2010
A novel 3780-point FFT.
Proceedings of the IEEE International Conference on Wireless Communications, 2010

An improved feedback cancelling method for on-channel repeater.
Proceedings of the IEEE International Conference on Wireless Communications, 2010


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