A Kernel Perspective for Regularizing Deep Neural Networks. - Alberto Bietti; Grégoire Mialon; Dexiong Chen; Julien Mairal (ICML, 2019)

Recurrent Kernel Networks. - Dexiong Chen; Laurent Jacob; Julien Mairal (NeurIPS, 2019)

Biological sequence modeling with convolutional kernel networks. - Dexiong Chen; Laurent Jacob; Julien Mairal (Bioinform., 2019)

MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning. - Zhijun Mai; Guosheng Hu; Dexiong Chen; Fumin Shen; Heng Tao Shen (CoRR, 2019)

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

An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention. - Grégoire Mialon; Dexiong Chen; Alexandre d'Aspremont; Julien Mairal (CoRR, 2020)

Modélisation de données structurées avec des machines profondes à noyaux et des applications en biologie computationnelle. (Structured Data Modeling with Deep Kernel Machines and Applications in Computational Biology). - Dexiong Chen (2020)

A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention. - Grégoire Mialon; Dexiong Chen; Alexandre d'Aspremont; Julien Mairal (ICLR, 2021)

GraphiT: Encoding Graph Structure in Transformers. - Grégoire Mialon; Dexiong Chen; Margot Selosse; Julien Mairal (CoRR, 2021)

Structure-Aware Transformer for Graph Representation Learning. - Dexiong Chen; Leslie O'Bray; Karsten M. Borgwardt (ICML, 2022)

Approximate Network Motif Mining Via Graph Learning. - Carlos G. Oliver; Dexiong Chen; Vincent Mallet; Pericles Philippopoulos; Karsten M. Borgwardt (CoRR, 2022)

Predicting in vitro single-neuron firing rates upon pharmacological perturbation using Graph Neural Networks. - Taehoon Kim; Dexiong Chen; Philipp Hornauer; Vishalini Emmenegger; Julian Bartram; Silvia Ronchi; Andreas Hierlemann; Manuel S. Schröter; Damian Roqueiro (Frontiers Neuroinformatics, 2022)

MetaMixUp: Learning Adaptive Interpolation Policy of MixUp With Metalearning. - Zhijun Mai; Guosheng Hu; Dexiong Chen; Fumin Shen; Heng Tao Shen (IEEE Trans. Neural Networks Learn. Syst., 2022)

Unsupervised Manifold Alignment with Joint Multidimensional Scaling. - Dexiong Chen; Bowen Fan; Carlos G. Oliver; Karsten M. Borgwardt (ICLR, 2023)

Fisher Information Embedding for Node and Graph Learning. - Dexiong Chen; Paolo Pellizzoni; Karsten M. Borgwardt (ICML, 2023)

ProteinShake: Building datasets and benchmarks for deep learning on protein structures. - Tim Kucera; Carlos G. Oliver; Dexiong Chen; Karsten M. Borgwardt (NeurIPS, 2023)

SURE: SUrvey REcipes for Building Reliable and Robust Deep Networks. - Yuting Li; Yingyi Chen; Xuanlong Yu; Dexiong Chen; Xi Shen 001 (CVPR, 2024)

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

Biomarker identification by interpretable maximum mean discrepancy. - Michael F. Adamer; Sarah C. Brüningk; Dexiong Chen; Karsten M. Borgwardt (Bioinform., 2024)

Endowing Protein Language Models with Structural Knowledge. - Dexiong Chen; Philip Hartout; Paolo Pellizzoni; Carlos G. Oliver; Karsten M. Borgwardt (CoRR, 2024)

HTR-VT: Handwritten Text Recognition with Vision Transformer. - Yuting Li; Dexiong Chen; Tinglong Tang; Xi Shen (CoRR, 2024)

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

Learning Long Range Dependencies on Graphs via Random Walks. - Dexiong Chen; Till Hendrik Schulz; Karsten M. Borgwardt (ICLR, 2025)

Detecting Antimicrobial Resistance Through MALDI-TOF Mass Spectrometry with Statistical Guarantees Using Conformal Prediction. - Nina Corvelo Benz; Lucas Miranda 002; Dexiong Chen; Janko Sattler; Karsten M. Borgwardt (RECOMB, 2025)

HTR-VT: Handwritten text recognition with vision transformer. - Yuting Li; Dexiong Chen; Tinglong Tang; Xi Shen 001 (Pattern Recognit., 2025)

Flatten Graphs as Sequences: Transformers are Scalable Graph Generators. - Dexiong Chen; Markus Krimmel; Karsten M. Borgwardt (CoRR, 2025)

Towards Fast Graph Generation via Autoregressive Noisy Filtration Modeling. - Markus Krimmel; Jenna Wiens; Karsten M. Borgwardt; Dexiong Chen (CoRR, 2025)