Chen, Dexiong

14 publications

TMLR 2026 Fast Graph Generation via Autoregressive Noisy Filtration Modeling Markus Krimmel, Jenna Wiens, Karsten Borgwardt, Dexiong Chen

NeurIPS 2025 Flatten Graphs as Sequences: Transformers Are Scalable Graph Generators Dexiong Chen, Markus Krimmel, Karsten Borgwardt

AISTATS 2025 Learning Laplacian Positional Encodings for Heterophilous Graphs Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens

ICLR 2025 Learning Long Range Dependencies on Graphs via Random Walks Dexiong Chen, Till Hendrik Schulz, Karsten Borgwardt

NeurIPS 2024 On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen, Karsten Borgwardt

CVPR 2024 SURE: SUrvey REcipes for Building Reliable and Robust Deep Networks Yuting Li, Yingyi Chen, Xuanlong Yu, Dexiong Chen, Xi Shen

ICML 2023 Fisher Information Embedding for Node and Graph Learning Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt

NeurIPS 2023 ProteinShake: Building Datasets and Benchmarks for Deep Learning on Protein Structures Tim Kucera, Carlos Oliver, Dexiong Chen, Karsten Borgwardt

ICLR 2023 Unsupervised Manifold Alignment with Joint Multidimensional Scaling Dexiong Chen, Bowen Fan, Carlos Oliver, Karsten Borgwardt

ICML 2022 Structure-Aware Transformer for Graph Representation Learning Dexiong Chen, Leslie O’Bray, Karsten Borgwardt

ICLR 2021 A Trainable Optimal Transport Embedding for Feature Aggregation and Its Relationship to Attention Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal

ICML 2020 Convolutional Kernel Networks for Graph-Structured Data Dexiong Chen, Laurent Jacob, Julien Mairal

ICML 2019 A Kernel Perspective for Regularizing Deep Neural Networks Alberto Bietti, Grégoire Mialon, Dexiong Chen, Julien Mairal

NeurIPS 2019 Recurrent Kernel Networks Dexiong Chen, Laurent Jacob, Julien Mairal