Chaitanya K. Joshi
Chaitanya K. Joshi
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Evaluating Representation Learning on the Protein Structure Universe
Open-source benchmarking framework for evaluating and scaling up protein structure representation learning methods, comparing
protein language models
and
Geometric GNNs
trained on AlphaFoldDB, the largest non-redundant protein structure corpus.
Arian R. Jamasb
,
Alex Moehead
,
Chaitanya K. Joshi
,
Zuobai Zhang
,
Kieran Didi
,
Simon V. Mathis
,
Charles Harris
,
Jian Tang
,
Jianlin Cheng
,
Pietro Liò
,
Tom L. Blundell
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On the Expressive Power of Geometric Graph Neural Networks
We propose a Geometric Weisfeiler-Leman test to study the expressive power of Geometric Graph Neural Networks and demonstrate the advantages of equivariant GNNs over invariant GNNs.
(Full paper at ICML 2023, and presented as an Oral at NeurIPS 2022 Workshop)
Chaitanya K. Joshi
,
Cristian Bodnar
,
Simon V. Mathis
,
Taco Cohen
,
Pietro Liò
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Video
NeurIPS Workshop Oral
Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds
We propose a point discriminative learning method for unsupervised representation learning on 3D point clouds to learn local and global shape features.
(3DV 2022)
Fayao Liu
,
Guosheng Lin
,
Chuan-Sheng Foo
,
Chaitanya K. Joshi
,
Jie Lin
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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?
(CP 2021)
Chaitanya K. Joshi
,
Quentin Cappart
,
Louis-Martin Rousseau
,
Thomas Laurent
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