| 2025 | AISTATS | Learning Laplacian Positional Encodings for Heterophilous Graphs. | Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens |
| 2025 | ICLR | Learning Long Range Dependencies on Graphs via Random Walks. | Dexiong Chen, Till Hendrik Schulz, Karsten M. Borgwardt |
| 2025 | RECOMB | Detecting Antimicrobial Resistance Through MALDI-TOF Mass Spectrometry with Statistical Guarantees Using Conformal Prediction. | Nina Corvelo Benz, Lucas Miranda, Dexiong Chen, Janko Sattler, Karsten M. Borgwardt |
| 2024 | CVPR | SURE: SUrvey REcipes for Building Reliable and Robust Deep Networks. | Yuting Li, Yingyi Chen, Xuanlong Yu, Dexiong Chen, Xi Shen |
| 2023 | ICLR | Unsupervised Manifold Alignment with Joint Multidimensional Scaling. | Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt |
| 2023 | ICML | Fisher Information Embedding for Node and Graph Learning. | Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt |
| 2022 | ICML | Structure-Aware Transformer for Graph Representation Learning. | Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt |
| 2021 | ICLR | A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention. | Grgoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal |
| 2020 | ICML | Convolutional Kernel Networks for Graph-Structured Data. | Dexiong Chen, Laurent Jacob, Julien Mairal |
| 2019 | ICML | A Kernel Perspective for Regularizing Deep Neural Networks. | Alberto Bietti, Grgoire Mialon, Dexiong Chen, Julien Mairal |
| 2019 | RECOMB | Biological Sequence Modeling with Convolutional Kernel Networks. | Dexiong Chen, Laurent Jacob, Julien Mairal |