Learning to Precode for Integrated Sensing and Communications Systems

no code implementations • 11 Mar 2023 • R. S. Prasobh Sankar, Sidharth S. Nair, Siddhant Doshi, Sundeep Prabhakar Chepuri

In this paper, we present an unsupervised learning neural model to design transmit precoders for integrated sensing and communication (ISAC) systems to maximize the worst-case target illumination power while ensuring a minimum signal-to-interference-plus-noise ratio (SINR) for all the users.

Graph Neural Networks with Parallel Neighborhood Aggregations for Graph Classification

1 code implementation • 22 Nov 2021 • Siddhant Doshi, Sundeep Prabhakar Chepuri

We focus on graph classification using a graph neural network (GNN) model that precomputes the node features using a bank of neighborhood aggregation graph operators arranged in parallel.

Graph Classification Graph Neural Network

Dr-COVID: Graph Neural Networks for SARS-CoV-2 Drug Repurposing

1 code implementation • 3 Dec 2020 • Siddhant Doshi, Sundeep Prabhakar Chepuri

In this work, we explore computational data-driven methods for drug repurposing and propose a dedicated graph neural network (GNN) based drug repurposing model, called Dr-COVID.

Graph Neural Network Link Prediction