research
∙
05/30/2023
Group Invariant Global Pooling
Much work has been devoted to devising architectures that build group-eq...
share
research
∙
05/24/2023
Multi-State RNA Design with Geometric Multi-Graph Neural Networks
Computational RNA design has broad applications across synthetic biology...
research
∙
01/23/2023
On the Expressive Power of Geometric Graph Neural Networks
The expressive power of Graph Neural Networks (GNNs) has been studied ex...
research
∙
11/09/2021
On Representation Knowledge Distillation for Graph Neural Networks
Knowledge distillation is a promising learning paradigm for boosting the...
research
∙
06/12/2020
Learning TSP Requires Rethinking Generalization
End-to-end training of neural network solvers for combinatorial problems...
research
∙
03/02/2020
Benchmarking Graph Neural Networks
Graph neural networks (GNNs) have become the standard toolkit for analyz...
research
∙
12/24/2019
Multi-Graph Transformer for Free-Hand Sketch Recognition
Learning meaningful representations of free-hand sketches remains a chal...
research
∙
10/16/2019
On Learning Paradigms for the Travelling Salesman Problem
We explore the impact of learning paradigms on training deep neural netw...
research
∙
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...
research
∙
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...
research
∙
06/22/2017