He Zhao

Greetings! This is my research page.

I’m a machine learning researcher at CSIRO’s Data61 and an adjunct research fellow at Monash University.

I’m interested in probabilistic approaches that improve robustness, generalisation, uncertainty estimation, and interpretation of machine/deep learning. I’m also into applications of optimal transport and Bayesian statistics (e.g., probabilistic models and variational inference) in the deep learning context.

I obtained my PhD working with Prof Wray Buntine and Dr Lan Du and then did my postdoc research with Prof Dinh Phung at Monash University.

🏆 Our paper led by Vy Vo won Best Student Paper - Research at KDD 2023.

Selected publications

[NeurIPS 2023] Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation

M.C. Jung, H. Zhao, J. Dipnall, L. Du

link

[NeurIPS 2023] NPCL: Neural Processes for Uncertainty-Aware Continual Learning

S. Jha, D. Gong, H. Zhao, L. Yao

link, code

[NeurIPS 2023] Enhancing Minority Classes by Mixing: An Adaptative Optimal Transport Approach for Long-tailed Classification

J. Gao, H. Zhao, Z. Li, D. Guo

link, code

[KDD 2023] Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations

V. Vo, T. Le, V. Nguyen, H. Zhao, E. Bonilla, G. Haffari, D. Phung

🏆 Best Student Paper - Research, link, code

[TMLR 2023] Generating Adversarial Examples with Task Oriented Multi-Objective Optimization

A. Bui, T. Le, H. Zhao, Q.H. Tran, P. Montague, D. Phung

Transactions on Machine Learning Research, link, code

[ICML 2023] Transformed Distribution Matching for Missing Value Imputation

H. Zhao, K. Sun, A. Dezfouli, E. Bonilla

link, code

[ICML 2023] Vector Quantized Wasserstein Auto-Encoder

L.T. Vuong, T. Le, H. Zhao, C. Zheng, M. Harandi, J. Cai, D. Phung

link, code

[NeurIPS 2022] Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture

M.C. Jung, H. Zhao, J. Dipnall, B. Gabbe, L. Du

link

[NeurIPS 2022] Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport

D. Guo, L. Tian, H. Zhao, M. Zhou, H. Zha

link, code

[NeurIPS 2022] Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification

D. Guo, Z. Li, M. Zheng, H. Zhao, M. Zhou, H. Zha

link, code

[ICLR 2022] A Unified Wasserstein Distributional Robustness Framework for Adversarial Training

A. Bui, T. Le, Q. Tran, H. Zhao, D. Phung

link, code

[ICLR 2022] Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings

D. Wang, D. Guo, H. Zhao, H. Zheng, K. Tanwisuth, B. Chen, M. Zhou

link, code

[AISTATS 2022] A Global Defense Approach via Adversarial Attack and Defense Risk Guaranteed Bounds

T. Le, A. Bui, M.T.T. Le, H. Zhao, P. Montague, Q. Tran, D. Phung

link

[AISTATS 2022] Particle-based Adversarial Local Distribution Regularization

T. Nguyen, T. Le, H. Zhao, J. Cai, D. Phung

link

[IJCAI 2021 Survey Track] Topic Modelling Meets Deep Neural Networks: A Survey

H. Zhao, D. Phung, V. Huynh, Y. Jin, L. Du, W. Buntine

link, arxiv

[ICLR 2021] Neural Topic Model via Optimal Transport

H. Zhao, D. Phung, V. Huynh, T. Le, W. Buntine

Spotlight, top 3% - 7%
link, code

[NeurIPS 2020] OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling

V. Huynh, H. Zhao, D. Phung

link

[ECCV 2020] Improving Adversarial Robustness by Enforcing Local and Global Compactness

A. Bui, T. Le, H. Zhao, P. Montague, O. de Vel, T. Abraham, D. Phung

link, arxiv, code

[AISTATS 2020] Variational Autoencoders for Sparse and Overdispersed Discrete Data

H. Zhao, P. Rai, L. Du, W. Buntine, D. Phung, M. Zhou

link, code

[NeurIPS 2018] Dirichlet Belief Networks for Topic Structure Learning

H. Zhao, L. Du, W. Buntine, M. Zhou

link, code

[ICML 2018] Inter and Intra Topic Structure Learning with Word Embeddings

H. Zhao, L. Du, W. Buntine, M. Zhou

link, code

[ACML 2017] A Word Embeddings Informed Focused Topic Model

H. Zhao, L. Du, W. Buntine

link, code

[ICDM 2017] MetaLDA: A Topic Model that Efficiently Incorporates Meta information

H. Zhao, L. Du, W. Buntine, G. Liu

link, arxiv, code

[ICML 2017] Leveraging Node Attributes for Incomplete Relational Data

H. Zhao, L. Du, W. Buntine

link, arxiv, code

He Zhao

Selected publications

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