Dexiong Chen

According to our database, Dexiong Chen authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

SURE: SUrvey REcipes for building reliable and robust deep networks.

Yuting Li, Yingyi Chen, Xuanlong Yu, Dexiong Chen, Xi Shen

CoRR, 2024

Endowing Protein Language Models with Structural Knowledge.

Dexiong Chen, Philip Hartout, Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt

CoRR, 2024

2023

ProteinShake: Building datasets and benchmarks for deep learning on protein structures.

Tim Kucera, Carlos G. Oliver, Dexiong Chen, Karsten M. Borgwardt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fisher Information Embedding for Node and Graph Learning.

Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt

Proceedings of the International Conference on Machine Learning, 2023

Unsupervised Manifold Alignment with Joint Multidimensional Scaling.

Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

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 Schröter, Damian Roqueiro

Frontiers Neuroinformatics, 2022

Approximate Network Motif Mining Via Graph Learning.

Carlos G. Oliver, Dexiong Chen, Vincent Mallet, Pericles Philippopoulos, Karsten M. Borgwardt

CoRR, 2022

Structure-Aware Transformer for Graph Representation Learning.

Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt

Proceedings of the International Conference on Machine Learning, 2022

2021

GraphiT: Encoding Graph Structure in Transformers.

Grégoire Mialon, Dexiong Chen, Margot Selosse, Julien Mairal

CoRR, 2021

A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention.

Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal

Proceedings of the 9th International Conference on Learning Representations, 2021

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

PhD thesis, 2020

An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention.

Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal

CoRR, 2020

Convolutional Kernel Networks for Graph-Structured Data.

Dexiong Chen, Laurent Jacob, Julien Mairal

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning.

Zhijun Mai, Guosheng Hu, Dexiong Chen, Fumin Shen, Heng Tao Shen

CoRR, 2019

Biological sequence modeling with convolutional kernel networks.

Dexiong Chen, Laurent Jacob, Julien Mairal

Bioinform., 2019

Recurrent Kernel Networks.

Dexiong Chen, Laurent Jacob, Julien Mairal

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Kernel Perspective for Regularizing Deep Neural Networks.

Alberto Bietti, Grégoire Mialon, Dexiong Chen, Julien Mairal

Proceedings of the 36th International Conference on Machine Learning, 2019