Chaitanya K. Joshi

Chaitanya K. Joshi

Research Engineer at A*STAR, Singapore

Publications

I am broadly interested in Deep Learning: my recent work focuses on Graph Neural Networks and their applications to Combinatorial Optimization. Previously, I worked on Attention & Memory Networks for Natural Langauge Processing.

Visit my Google Scholar profile for up-to-date papers and citations.


2020

Learning TSP Requires Rethinking Generalization

Chaitanya K. Joshi, Quentin Cappart, Louis-Martin Rousseau, Thomas Laurent, and Xavier Bresson
ArXiv preprint, 2020 (Under review)
Learning TSP Requires Rethinking Generalization

tl;dr What architectures, inductive biases and learning paradigms enable zero-shot generalization to large-scale instances in learning-driven TSP solvers?

Benchmarking Graph Neural Networks

Vijay Prakash Dwivedi*, Chaitanya K. Joshi*, Thomas Laurent, Yoshua Bengio, and Xavier Bresson
ArXiv preprint, 2020 (Under review)
Benchmarking GNNs

tl;dr Open-source benchmarking framework to identify scalable and powerful GNN architectures, and track the progress of graph representation learning.


2019

Multi-Graph Transformer for Free-Hand Sketch Recognition

Peng Xu, Chaitanya K. Joshi, and Xavier Bresson
ArXiv preprint, 2019 (Under review)

tl;dr Representation learning for free-hand drawings using GNNs and Transformers.

On Learning Paradigms for the Travelling Salesman Problem

Chaitanya K. Joshi, Thomas Laurent, and Xavier Bresson
NeurIPS 2019, Graph Representation Learning Workshop

tl;dr How do learning paradigms impact zero-shot generalization to large-scale instances in learning-driven TSP solvers?

An Efficient Graph ConvNet for the Travelling Salesman Problem

Chaitanya K. Joshi, Thomas Laurent, and Xavier Bresson
INFORMS Annual Meeting, 2019 (Invited Talk); ArXiv preprint, 2019
An Efficient GCN for TSP

tl;dr Deep Graph ConvNets paired with parallelized graph search can learn TSP up to few hundred cities, but fall short of classical solvers.

Working Women and Caste in India: A Study of Social Disadvantage using Feature Attribution

Kuhu Joshi and Chaitanya K. Joshi
ICLR 2019, AI for Social Good Workshop

tl;dr Feature attribution to interpret decision tree models and study the generational imact of caste on women’s work force participation in India.

Graph ConvNets for the Travelling Salesman Problem

Chaitanya K. Joshi
Bachelor’s Thesis, Nanyang Technological University, Singapore
(:trophy: Best Final Year Thesis Gold Medal, 2018-19)


2018

Question-answering and Chatbots using Memory Networks

Chaitanya K. Joshi
Book chapter, Hands-On NLP with Python (R. Arumugam and R. Shanmugamani, eds.), pp. 175-199, Packt Publishers, 2018


2017

Personalization in Goal-oriented Dialog

Chaitanya K. Joshi, Fei Mi, and Boi Faltings
NeurIPS 2017, Conversational AI Workshop

tl;dr New datasets and Memory Network architectures for studying personalized dialog systems based on user profiles.

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