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09/18/2023
Asynchronous Perception-Action-Communication with Graph Neural Networks
Collaboration in large robot swarms to achieve a common global objective...
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08/13/2023
Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles
This paper addresses the problem of active collaborative localization in...
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07/21/2023
Transferability of Convolutional Neural Networks in Stationary Learning Tasks
Recent advances in hardware and big data acquisition have accelerated th...
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07/11/2023
Intrinsically motivated graph exploration using network theories of human curiosity
Intrinsically motivated exploration has proven useful for reinforcement ...
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06/20/2023
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
We study the problem of computing an optimal policy of an infinite-horiz...
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06/14/2023
A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand
Despite the prevalence of wireless connectivity in urban areas around th...
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06/04/2023
Resilient Constrained Learning
When deploying machine learning solutions, they must satisfy multiple re...
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05/29/2023
Active Collaborative Localization in Heterogeneous Robot Teams
Accurate and robust state estimation is critical for autonomous navigati...
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05/29/2023
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs
This paper studies the relationship between a graph neural network (GNN)...
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05/27/2023
Explainable Brain Age Prediction using coVariance Neural Networks
In computational neuroscience, there has been an increased interest in d...
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05/24/2023
Stochastic Unrolled Federated Learning
Algorithm unrolling has emerged as a learning-based optimization paradig...
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05/02/2023
Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features
Graph convolutional networks (GCN) leverage topology-driven graph convol...
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03/20/2023
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back
In this work we introduce a convolution operation over the tangent bundl...
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01/23/2023
Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense
In this work, we study the problem of decentralized multi-agent perimete...
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12/15/2022
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs
In this paper we propose a pooling approach for convolutional informatio...
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11/20/2022
Convolutional Filtering on Sampled Manifolds
The increasing availability of geometric data has motivated the need for...
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11/11/2022
Stable and Transferable Hyper-Graph Neural Networks
We introduce an architecture for processing signals supported on hypergr...
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10/28/2022
A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks
We consider a radio resource management (RRM) problem in a multi-user wi...
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10/28/2022
Predicting Brain Age using Transferable coVariance Neural Networks
The deviation between chronological age and biological age is a well-rec...
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10/28/2022
Learning with Multigraph Convolutional Filters
In this paper, we introduce a convolutional architecture to perform lear...
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10/28/2022
Space-Time Graph Neural Networks with Stochastic Graph Perturbations
Space-time graph neural networks (ST-GNNs) are recently developed archit...
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10/27/2022
Neural Networks with Quantization Constraints
Enabling low precision implementations of deep learning models, without ...
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10/27/2022
Multi-task Bias-Variance Trade-off Through Functional Constraints
Multi-task learning aims to acquire a set of functions, either regressor...
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10/27/2022
Training Graph Neural Networks on Growing Stochastic Graphs
Graph Neural Networks (GNNs) rely on graph convolutions to exploit meani...
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10/27/2022
Deep Convolutional Neural Networks for Multi-Target Tracking: A Transfer Learning Approach
Multi-target tracking (MTT) is a traditional signal processing task, whe...
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10/26/2022
Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back
In this work we introduce a convolution operation over the tangent bundl...
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10/17/2022
Unsupervised Optimal Power Flow Using Graph Neural Networks
Optimal power flow (OPF) is a critical optimization problem that allocat...
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10/01/2022
Convolutional Neural Networks on Manifolds: From Graphs and Back
Geometric deep learning has gained much attention in recent years due to...
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10/01/2022
Learning Globally Smooth Functions on Manifolds
Smoothness and low dimensional structures play central roles in improvin...
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10/01/2022
Federated Representation Learning via Maximal Coding Rate Reduction
We propose a federated methodology to learn low-dimensional representati...
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09/29/2022
Automatic Data Augmentation via Invariance-Constrained Learning
Underlying data structures, such as symmetries or invariances to transfo...
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09/24/2022
Learning Decentralized Strategies for a Perimeter Defense Game with Graph Neural Networks
We consider the problem of finding decentralized strategies for multi-ag...
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09/23/2022
Convolutional Learning on Multigraphs
Graph convolutional learning has led to many exciting discoveries in div...
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07/08/2022
Stability of Aggregation Graph Neural Networks
In this paper we study the stability properties of aggregation graph neu...
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07/05/2022
State-Augmented Learnable Algorithms for Resource Management in Wireless Networks
We consider resource management problems in multi-user wireless networks...
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05/31/2022
coVariance Neural Networks
Graph neural networks (GNN) are an effective framework that exploit inte...
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05/19/2022
Graph Neural Networks Are More Powerful Than we Think
Graph Neural Networks (GNNs) are powerful convolutional architectures th...
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05/19/2022
Learning Graph Structure from Convolutional Mixtures
Machine learning frameworks such as graph neural networks typically rely...
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03/07/2022
Learning Resilient Radio Resource Management Policies with Graph Neural Networks
We consider the problems of downlink user selection and power control in...
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02/08/2022
A Lagrangian Duality Approach to Active Learning
We consider the batch active learning problem, where only a subset of th...
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12/14/2021
Learning Connectivity-Maximizing Network Configurations
In this work we propose a data-driven approach to optimizing the algebra...
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12/09/2021
Transferability Properties of Graph Neural Networks
Graph neural networks (GNNs) are deep convolutional architectures consis...
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10/10/2021
Stability of Neural Networks on Manifolds to Relative Perturbations
Graph Neural Networks (GNNs) show impressive performance in many practic...
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10/07/2021
Training Stable Graph Neural Networks Through Constrained Learning
Graph Neural Networks (GNN) rely on graph convolutions to learn features...
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10/06/2021
Space-Time Graph Neural Networks
We introduce space-time graph neural network (ST-GNN), a novel GNN archi...
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09/30/2021
Coverage Control in Multi-Robot Systems via Graph Neural Networks
This paper develops a decentralized approach to mobile sensor coverage b...
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08/23/2021
Convolutional Filtering and Neural Networks with Non Commutative Algebras
In this paper we provide stability results for algebraic neural networks...
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07/19/2021
Wide and Deep Graph Neural Network with Distributed Online Learning
Graph neural networks (GNNs) are naturally distributed architectures for...
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06/24/2021
Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks
In this paper, we present a perception-action-communication loop design ...
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06/19/2021
