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05/30/2023
Group Invariant Global Pooling
Much work has been devoted to devising architectures that build group-eq...
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05/24/2023
Multi-State RNA Design with Geometric Multi-Graph Neural Networks
Computational RNA design has broad applications across synthetic biology...
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01/23/2023
On the Expressive Power of Geometric Graph Neural Networks
The expressive power of Graph Neural Networks (GNNs) has been studied ex...
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11/09/2021
On Representation Knowledge Distillation for Graph Neural Networks
Knowledge distillation is a promising learning paradigm for boosting the...
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06/12/2020
Learning TSP Requires Rethinking Generalization
End-to-end training of neural network solvers for combinatorial problems...
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03/02/2020
Benchmarking Graph Neural Networks
Graph neural networks (GNNs) have become the standard toolkit for analyz...
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12/24/2019
Multi-Graph Transformer for Free-Hand Sketch Recognition
Learning meaningful representations of free-hand sketches remains a chal...
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10/16/2019
On Learning Paradigms for the Travelling Salesman Problem
We explore the impact of learning paradigms on training deep neural netw...
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06/04/2019
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
This paper introduces a new learning-based approach for approximately so...
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04/27/2019
Working women and caste in India: A study of social disadvantage using feature attribution
Women belonging to the socially disadvantaged caste-groups in India have...
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06/22/2017
