By Dr Rohitash Chandra

Working Papers

Chandra R, An affective computational model for machine consciousness, http://dx.doi.org, http://arxiv.org/abs/1701.00349v1

Chandra R; Bhagat A; Maharana M; Krivitsky PN, Bayesian graph convolutional neural networks via tempered MCMC, http://dx.doi.org, http://arxiv.org/abs/2104.08438v1

Chandra R; Krishna A, COVID-19 sentiment analysis via deep learning during the rise of novel cases, http://dx.doi.org, http://arxiv.org/abs/2104.10662v1

Chandra R; Jain A; Chauhan DS, Deep learning via LSTM models for COVID-19 infection forecasting in India, http://dx.doi.org, http://arxiv.org/abs/2101.11881v1

Tiwari A; Gupta R; Chandra R, Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown, http://dx.doi.org, http://arxiv.org/abs/2102.10551v1

Abel D; Gavidi B; Rollings N; Chandra R, Development of an Android Application for an Electronic Medical Record System in an Outpatient Environment for Healthcare in Fiji, http://dx.doi.org, http://arxiv.org/abs/1503.00810v1

Renanse A; Chandra R; Sharma A, Memory Capacity of Neural Turing Machines with Matrix Representation, http://dx.doi.org, http://arxiv.org/abs/2104.07454v1

Reddy E; Kumar S; Rollings N; Chandra R, Mobile Application for Dengue Fever Monitoring and Tracking via GPS: Case Study for Fiji, http://dx.doi.org, http://arxiv.org/abs/1503.00814v1

Chandra R; Jain M; Maharana M; Krivitsky PN, Revisiting Bayesian Autoencoders with MCMC, http://dx.doi.org, http://arxiv.org/abs/2104.05915v1

Chandra R, Towards prediction of rapid intensification in tropical cyclones with recurrent neural networks, http://dx.doi.org, http://arxiv.org/abs/1701.04518v1

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