| 2025 | ICLR | Multi-Label Node Classification with Label Influence Propagation. | Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He |
| 2024 | ICLR | Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision. | Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen |
| 2024 | ICLR | Partitioning Message Passing for Graph Fraud Detection. | Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen |
| 2024 | IJCNN | Simultaneously Detecting Node and Edge Level Anomalies on Heterogeneous Attributed Graphs. | Rizal Fathony, Jenn Ng, Jia Chen |
| 2023 | IJCNN | Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs. | Rizal Fathony, Jenn Ng, Jia Chen |
| 2023 | PAKDD | Fairness for Robust Learning to Rank. | Omid Memarrast, Ashkan Rezaei, Rizal Fathony, Brian D. Ziebart |
| 2021 | ICLR | Multiplicative Filter Networks. | Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter |
| 2020 | AAAI | Fairness for Robust Log Loss Classification. | Ashkan Rezaei, Rizal Fathony, Omid Memarrast, Brian D. Ziebart |
| 2020 | AISTATS | AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning. | Rizal Fathony, J. Zico Kolter |
| 2018 | ICML | Efficient and Consistent Adversarial Bipartite Matching. | Rizal Fathony, Sima Behpour, Xinhua Zhang, Brian D. Ziebart |