ESC

Publications

Peer-reviewed papers and preprints. Filter by year or topic.

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2026

Harnessing Trust in Directed Graphs: Redefining Robustness of Graph Learning

Zhichao Hou, Xitong Zhang, Wei Wang, Charu C. Aggarwal, Xiaorui Liu

ACM Transactions on Knowledge Discovery from Data (TKDD) #trustworthy-ai#graph-learning

ICLR 2026 Paper ↗

Fine-Grained Iterative Adversarial Attacks with Limited Computation Budget

Zhichao Hou, Weizhi Gao, Xiaorui Liu

International Conference on Learning Representations (ICLR) #trustworthy-ai#adversarial-robustness#efficient-ai

ICLR 2026 OpenReview ↗

Hierarchical Multi-Scale Molecular Conformer Generation with Structural Awareness

Jiapeng Hu, Weizhi Gao, Zhichao Hou, Xiaorui Liu

International Conference on Learning Representations (ICLR) #ai-for-science#generative-models

2025

ICLR 2025 🏆 SPOTLIGHT Paper ↗GitHub ↗Poster ↗

Robustness Reprogramming for Representation Learning

Zhichao Hou, MohamadAli Torkamani, Hamid Krim, Xiaorui Liu

Top 1.4% of 11,670 submissions · International Conference on Learning Representations (ICLR) #trustworthy-ai#adversarial-robustness

ICML 2025 Paper ↗

Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization

Weizhi Gao, Zhichao Hou, Junqi Yin, Feiyi Wang, Linyu Peng, Xiaorui Liu

International Conference on Machine Learning (ICML) #efficient-ai#generative-models

ICLR Workshop 2025 Paper ↗

Post-hoc Interpretability Illumination for Scientific Interaction Discovery

Ling Zhang, Zhichao Hou, Tingxiang Ji, Yuanyuan Xu, Runze Li

ICLR Workshop XAI4Science #ai-for-science

Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs

Wei Wang, Zhichao Hou, Xiaorui Liu, Xinxia Peng

MABM #ai-for-science#llm#bioinformatics

Preprint 2025 Paper ↗

Boosting Adversarial Robustness and Generalization with Structural Prior

Zhichao Hou, Weizhi Gao, Hamid Krim, Xiaorui Liu

Preprint #trustworthy-ai#adversarial-robustness

2024

ProTransformer: Robustify Transformers via Plug-and-Play Paradigm

Zhichao Hou, Weizhi Gao, Yuchen Shen, Feiyi Wang, Xiaorui Liu

Neural Information Processing Systems (NeurIPS) #trustworthy-ai#transformers#adversarial-robustness

Robust Graph Neural Networks via Unbiased Aggregation

Zhichao Hou, Ruiqi Feng, Tyler Derr, Xiaorui Liu

Neural Information Processing Systems (NeurIPS) #trustworthy-ai#graph-learning

NeurIPS 2024 Paper ↗GitHub ↗

Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

Weizhi Gao, Zhichao Hou, Han Xu, Xiaorui Liu

Neural Information Processing Systems (NeurIPS) #trustworthy-ai#adversarial-robustness#efficient-ai

IEEE BigData 2024 Paper ↗GitHub ↗

Automated Polynomial Filter Learning for Graph Neural Networks

Wendi Yu, Zhichao Hou, Xiaorui Liu

IEEE International Conference on Big Data (IEEE BigData) #efficient-ai#graph-learning

Briefings in Bioinformatics 2024 Paper ↗GitHub ↗

Incorporating Network Diffusion and Peak Location Information for Better Single-Cell ATAC-seq Data Analysis

Jiating Yu, Jiacheng Leng, Zhichao Hou, Duanchen Sun, Ling-Yun Wu

Briefings in Bioinformatics #ai-for-science#bioinformatics

Preprint 2024 Paper ↗GitHub ↗

HLogformer: A Hierarchical Transformer for Representing Log Data

Zhichao Hou, Mina Ghashami, Mikhail Kuznetsov, MohamadAli Torkamani

Preprint #efficient-ai#transformers

2023

NeurIPS 2023 Paper ↗GitHub ↗

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

Liming Wu*, Zhichao Hou*, Jirui Yuan, Yu Rong, Wenbing Huang

Neural Information Processing Systems (NeurIPS) · * denotes equal contribution #ai-for-science#graph-learning

BMC Bioinformatics 2023 Paper ↗GitHub ↗

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene Discovery

Zhichao Hou, Jiacheng Leng, Jiating Yu, Zheng Xia, Ling-Yun Wu

BMC Bioinformatics #ai-for-science#bioinformatics