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05/31/2023
Explanations as Features: LLM-Based Features for Text-Attributed Graphs
Representation learning on text-attributed graphs (TAGs) has become a cr...
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05/25/2023
Feature Collapse
We formalize and study a phenomenon called feature collapse that makes p...
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12/27/2022
A Generalization of ViT/MLP-Mixer to Graphs
Graph Neural Networks (GNNs) have shown great potential in the field of ...
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06/01/2022
Learning to Untangle Genome Assembly with Graph Convolutional Networks
A quest to determine the complete sequence of a human DNA from telomere ...
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05/29/2022
A Model of One-Shot Generalization
We provide a theoretical framework to study a phenomenon that we call on...
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05/09/2022
The Forgotten Margins of AI Ethics
How has recent AI Ethics literature addressed topics such as fairness an...
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03/02/2022
Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem
The traveling salesman problem is a fundamental combinatorial optimizati...
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10/15/2021
Graph Neural Networks with Learnable Structural and Positional Representations
Graph neural networks (GNNs) have become the standard learning architect...
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03/04/2021
The Transformer Network for the Traveling Salesman Problem
The Traveling Salesman Problem (TSP) is the most popular and most studie...
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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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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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10/02/2019
A Mutation-based Approach for Assessing Weight Coverage of a Path Planner
Autonomous cars are subjected to several different kind of inputs (other...
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06/08/2019
A Two-Step Graph Convolutional Decoder for Molecule Generation
We propose a simple auto-encoder framework for molecule generation. The ...
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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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04/15/2019
GraphTSNE: A Visualization Technique for Graph-Structured Data
We present GraphTSNE, a novel visualization technique for graph-structur...
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12/29/2017
The Multilinear Structure of ReLU Networks
We study the loss surface of neural networks equipped with a hinge loss ...
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12/05/2017
Deep linear neural networks with arbitrary loss: All local minima are global
We consider deep linear networks with arbitrary differentiable loss. We ...
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11/20/2017
Residual Gated Graph ConvNets
Graph-structured data such as functional brain networks, social networks...
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12/19/2016
A recurrent neural network without chaos
We introduce an exceptionally simple gated recurrent neural network (RNN...
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06/19/2015
Enhanced Lasso Recovery on Graph
This work aims at recovering signals that are sparse on graphs. Compress...
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11/24/2014
Consistency of Cheeger and Ratio Graph Cuts
This paper establishes the consistency of a family of graph-cut-based al...
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06/05/2013
