Chaitanya K. Joshi
Chaitanya K. Joshi
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Graph Neural Networks
Learning TSP 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
Learning TSP Requires Rethinking Generalization
This talk discusses our recent work on deep learning for TSP and the challenge of zero-shot generalization for large-scale and real-world routing problems.
Jun 8, 2021 12:00 AM
CORS 2021 (Host: Maxime Gasse)
Chaitanya K. Joshi
Project
Slides
Video
Multi-Graph Transformer for Free-Hand Sketch Recognition
Representation learning for free-hand drawings using GNNs and Transformers.
Peng Xu
,
Chaitanya K. Joshi
,
Xavier Bresson
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DOI
Blog
Graph Neural Networks: Benchmarks and Future Directions
I discuss state-of-the-art Graph Neural Network architectures and introduce our recent work on Benchmarking GNNs, along with some interesting future directions.
Sep 24, 2020 12:00 AM
DSO National Laboratories (Host: Chieu Hai Leong)
Chaitanya K. Joshi
Project
Slides
Benchmarking Graph Neural Networks
Open-source benchmarking framework to identify scalable and powerful GNN architectures, and track the progress of graph representation learning research.
(1500+ GitHub Stars)
Vijay Prakash Dwivedi
,
Chaitanya K. Joshi
,
Thomas Laurent
,
Yoshua Bengio
,
Xavier Bresson
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Press
Transformers are Graph Neural Networks
Exploring the connection between Transformer models such as GPT and BERT for Natural Language Processing, and Graph Neural Networks.
(50,000+ readers on The Gradient)
Chaitanya K. Joshi
Last updated on Jun 21, 2021
12 min read
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The Gradient
Towards Data Science
Graph Neural Networks for the Travelling Salesman Problem
This talk introduces a recent line of work using Graph Neural Networks to directly ‘learn’ good heuristics for TSP in an end-to-end manner.
Oct 22, 2019 12:00 AM
INFORMS Annual Meeting 2019 (Host: Quentin Cappart)
Chaitanya K. Joshi
Project
Slides
On Learning Paradigms for the Travelling Salesman Problem
How do learning paradigms impact zero-shot generalization to large-scale instances in learning-driven TSP solvers?
Chaitanya K. Joshi
,
Thomas Laurent
,
Xavier Bresson
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Poster
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Deep Graph ConvNets paired with parallelized graph search can learn TSP up to few hundred cities, but fall short of classical solvers.
Chaitanya K. Joshi
,
Thomas Laurent
,
Xavier Bresson
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Combinatorial Optimization
Neural Networks for learning to solve combinatorial optimization problems.
Chaitanya K. Joshi
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