Yang Zhao

Orcid: 0000-0001-5883-2799

Affiliations:
  • Tsinghua University, Department of Electronic Engineering, Beijing, China


According to our database1, Yang Zhao authored at least 15 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Activity cliff-aware reinforcement learning for de novo drug design.
J. Cheminformatics, December, 2025

TransDiffSBDD: Causality-Aware Multi-Modal Structure-Based Drug Design.
CoRR, March, 2025

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Hamiltonian diversity: effectively measuring molecular diversity by shortest Hamiltonian circuits.
J. Cheminformatics, December, 2024

When Will Gradient Regularization Be Harmful?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Role Taxonomy of Units in Deep Neural Networks.
Proceedings of UniReps: the First Workshop on Unifying Representations in Neural Models, 2023

De novo Drug Design using Reinforcement Learning with Multiple GPT Agents.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

De novo Drug Design against SARS-CoV-2 Protein Targets using SMILES-based Deep Reinforcement Learning.
Proceedings of the 2023 11th International Conference on Information Technology: IoT and Smart City, 2023

2022
SS-SAM : Stochastic Scheduled Sharpness-Aware Minimization for Efficiently Training Deep Neural Networks.
CoRR, 2022

Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning.
Proceedings of the International Conference on Machine Learning, 2022

Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Neighborhood Region Smoothing Regularization for Finding Flat Minima in Deep Neural Networks.
Proceedings of the Computer Vision - ACCV 2022, 2022

2021
Analyzing and Quantifying Generalization in Convolutional Neural Networks.
CoRR, 2021

Quantitative Effectiveness Assessment and Role Categorization of Individual Units in Convolutional Neural Networks.
CoRR, 2021

2020
A topological approach to exploring convolutional neural networks.
CoRR, 2020


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