16 citations · 32 across the 12 of their papers we have counts for
14 papers
Automatic Detection of COVID-19 from Chest X-ray Images Using Deep Learning Model
Alloy Das, Rohit Agarwal, Rituparna Singh +2
The infectious disease caused by novel corona virus (2019-nCoV) has been widely spreading since last year and has shaken the entire world. It has caused an unprecedented effect on…
Learning Non-myopic Power Allocation in Constrained Scenarios
Arindam Chowdhury, Santiago Paternain, Gunjan Verma +2
We propose a learning-based framework for efficient power allocation in ad hoc interference networks under episodic constraints. The problem of optimal power allocation -- for maxi…
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks
Arindam Chowdhury, Gunjan Verma, Ananthram Swami +1
We develop an efficient and near-optimal solution for beamforming in multi-user multiple-input-multiple-output single-hop wireless ad-hoc interference networks. Inspired by the wei…
ML-aided power allocation for Tactical MIMO
Arindam Chowdhury, Gunjan Verma, Chirag Rao +2
We study the problem of optimal power allocation in single-hop multi-antenna ad-hoc wireless networks. A standard technique to solve this problem involves optimizing a tri-convex f…
Label Propagation across Graphs: Node Classification using Graph Neural Tangent Kernels
Artun Bayer, Arindam Chowdhury, Santiago Segarra
Graph neural networks (GNNs) have achieved superior performance on node classification tasks in the last few years. Commonly, this is framed in a transductive semi-supervised learn…
Stability Analysis of Unfolded WMMSE for Power Allocation
Arindam Chowdhury, Fernando Gama, Santiago Segarra
Power allocation is one of the fundamental problems in wireless networks and a wide variety of algorithms address this problem from different perspectives. A common element among t…
GIST: Distributed Training for Large-Scale Graph Convolutional Networks
Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury +4
The graph convolutional network (GCN) is a go-to solution for machine learning on graphs, but its training is notoriously difficult to scale both in terms of graph size and the num…
Efficient power allocation using graph neural networks and deep algorithm unfolding
Arindam Chowdhury, Gunjan Verma, Chirag Rao +2
We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we propose a hybrid neural architecture inspired by the algorithm…
Unfolding WMMSE using Graph Neural Networks for Efficient Power Allocation
Arindam Chowdhury, Gunjan Verma, Chirag Rao +2
We study the problem of optimal power allocation in a single-hop ad hoc wireless network. In solving this problem, we depart from classical purely model-based approaches and propos…
Accelerography: Feasibility of Gesture Typing using Accelerometer
Arindam Roy Chowdhury, Abhinandan Dalal, Shubhajit Sen
In this paper, we aim to look into the feasibility of constructing alphabets using gestures. The main idea is to construct gestures, that are easy to remember, not cumbersome to re…
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks
Monika Sharma, Shikha Gupta, Arindam Chowdhury +1
Despite the improvements in perception accuracies brought about via deep learning, developing systems combining accurate visual perception with the ability to reason over the visua…
Deep Reader: Information extraction from Document images via relation extraction and Natural Language
Vishwanath D, Rohit Rahul, Gunjan Sehgal +6
Recent advancements in the area of Computer Vision with state-of-art Neural Networks has given a boost to Optical Character Recognition (OCR) accuracies. However, extracting charac…
Reading Industrial Inspection Sheets by Inferring Visual Relations
Rohit Rahul, Arindam Chowdhury, Animesh +2
The traditional mode of recording faults in heavy factory equipment has been via hand marked inspection sheets, wherein a machine engineer manually marks the faulty machine regions…
An Efficient End-to-End Neural Model for Handwritten Text Recognition
Arindam Chowdhury, Lovekesh Vig
Offline handwritten text recognition from images is an important problem for enterprises attempting to digitize large volumes of handmarked scanned documents/reports. Deep recurren…