Chaitanya K. Joshi
Chaitanya K. Joshi
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On Representation Knowledge Distillation for Graph Neural Networks
Strategies for distilling representational knowledge from expressive yet cumbersome-to-deploy GNNs to resource-efficient and lightweight architectures.
(IEEE TNNLS)
Chaitanya K. Joshi
,
Fayao Liu
,
Xu Xun
,
Jie Lin
,
Chuan-Sheng Foo
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DOI
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Hypergraph Factorisation for Multi-tissue Gene Expression Imputation
HYFA (Hypergraph Factorisation) jointly imputates multi-tissue and cell-type gene expression via a specialised graph neural network operating on a hypergraph of individuals, metagenes, and tissues.
(Nature Machine Intelligence, cover article)
Ramon Viñas
,
Chaitanya K. Joshi
,
Dobrik Georgiev
,
Phillip Lin
,
Bianca Dumitrascu
,
Eric R. Gamazon
,
Pietro Liò
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DOI
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Learning the Travelling Salesperson Problem Requires Rethinking Generalization
We study zero-shot generalization to large-scale instances in neural network-driven solvers for the Travelling Salesman Problem: what architectures, inductive biases and learning paradigms enable better generalization?
(Invited submission to the Constraints Journal)
Chaitanya K. Joshi
,
Quentin Cappart
,
Louis-Martin Rousseau
,
Thomas Laurent
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DOI
Blog
Multi-Graph Transformer for Free-Hand Sketch Recognition
Representation learning for free-hand drawings using GNNs and Transformers.
(IEEE TNNLS)
Peng Xu
,
Chaitanya K. Joshi
,
Xavier Bresson
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DOI
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Benchmarking Graph Neural Networks
Open-source benchmarking framework to identify scalable and powerful GNN architectures, and track the progress of graph representation learning research.
(500+ citations, 2000+ GitHub stars)
Vijay Prakash Dwivedi
,
Chaitanya K. Joshi
,
Luu Anh Tuan
,
Thomas Laurent
,
Yoshua Bengio
,
Xavier Bresson
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