Rohitash Chandra

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 109

Top Venues

Publications

Hamish Haggerty, Rohitash Chandra
Self-supervised learning for skin cancer diagnosis with limited training data. CoRR (2024)
Rohitash Chandra, Joshua A. Simmons
Bayesian Neural Networks via MCMC: A Python-Based Tutorial. IEEE Access 12 (2024)
Rohitash Chandra, Abhishek Tiwari, Naman Jain, Sushrut Badhe
Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon on the Mount. IEEE Access 12 (2024)
Ratneel Deo, Jody M. Webster, Tristan Salles, Rohitash Chandra
ReefCoreSeg: A Clustering-Based Framework for Multi-Source Data Fusion for Segmentation of Reef Drill Cores. IEEE Access 12 (2024)
Rohitash Chandra, Baicheng Zhu, Qingying Fang, Eka Shinjikashvili
Large language models for sentiment analysis of newspaper articles during COVID-19: The Guardian. CoRR (2024)
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation. Expert Syst. Appl. 244 (2024)
Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. ICRA (2024)
Azal Ahmad Khan, Salman Hussain, Rohitash Chandra
A Quantum-Inspired Predator-Prey Algorithm for Real-Parameter Optimization. Algorithms 17 (1) (2024)
Siddharth Khedkar, R. Willem Vervoort, Rohitash Chandra
Evaluation of deep learning models for Australian climate extremes: prediction of streamflow and floods. CoRR (2024)
Mahek Vora, Tom Blau, Vansh Kachhwal, Ashu M. G. Solo, Rohitash Chandra
Large language model for Bible sentiment analysis: Sermon on the Mount. CoRR (2024)
Yuhao Ke, Ranran Bian, Rohitash Chandra
A unified machine learning framework for basketball team roster construction: NBA and WNBA. Appl. Soft Comput. 153 (2024)
Chaarvi Bansal, P. R. Deepa, Vinti Agarwal, Rohitash Chandra
A clustering and graph deep learning-based framework for COVID-19 drug repurposing. Expert Syst. Appl. 249 (2024)
Eric Chen, Martin S. Andersen, Rohitash Chandra
Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels. Environ. Model. Softw. 178 (2024)
Nhat Minh Nguyen, Minh-Ngoc Tran, Rohitash Chandra
Sequential reversible jump MCMC for dynamic Bayesian neural networks. Neurocomputing 564 (2024)
Sandeep Nagar, Ehsan Farahbakhsh, Joseph L. Awange, Rohitash Chandra
Remote sensing framework for geological mapping via stacked autoencoders and clustering. CoRR (2024)
Arpit Kapoor, Sahani Pathiraja, Lucy Marshall, Rohitash Chandra
DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling. Environ. Model. Softw. 169 (2023)
George Bai, Rohitash Chandra
Gradient boosting Bayesian neural networks via Langevin MCMC. Neurocomputing 558 (2023)
Rohitash Chandra, Jayesh Sonawane, Janhavi Lande, Cathy Yu
An analysis of vaccine-related sentiments from development to deployment of COVID-19 vaccines. CoRR (2023)
Janhavi Lande, Arti Pillay, Rohitash Chandra
Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron. CoRR (2023)
Rohitash Chandra, Royce Chen, Joshua Simmons
Bayesian neural networks via MCMC: a Python-based tutorial. CoRR (2023)
Tianyi Wang, Rodney Beard, John Hawkins, Rohitash Chandra
Recursive deep learning framework for forecasting the decadal world economic outlook. CoRR (2023)
Saharsh Barve, Jody M. Webster, Rohitash Chandra
Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing. Inf. 14 (7) (2023)
Animesh Renanse, Alok Sharma, Rohitash Chandra
Memory capacity of recurrent neural networks with matrix representation. Neurocomputing 560 (2023)
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation. CoRR (2023)
Chaarvi Bansal, Rohitash Chandra, Vinti Agarwal, P. R. Deepa
A clustering and graph deep learning-based framework for COVID-19 drug repurposing. CoRR (2023)
Amit Krishan Kumar, Snigdha Jain, Shirin Jain, M. Ritam, Yuanqing Xia, Rohitash Chandra
Physics-informed neural entangled-ladder network for inhalation impedance of the respiratory system. Comput. Methods Programs Biomed. 231 (2023)
Saharsh Barve, Jody M. Webster, Rohitash Chandra
Reef-insight: A framework for reef habitat mapping with clustering methods via remote sensing. CoRR (2023)
Mahsa Tavakoli, Rohitash Chandra, Fengrui Tian, Cristián Bravo
Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams. CoRR (2023)
Akshat Shukla, Chaarvi Bansal, Sushrut Badhe, Mukul Ranjan, Rohitash Chandra
An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis. CoRR (2023)
Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. CoRR (2023)
Arpit Kapoor, Anshul Negi, Lucy Marshall, Rohitash Chandra
Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks. Environ. Model. Softw. 162 (2023)
Akshat Shukla, Chaarvi Bansal, Sushrut Badhe, Mukul Ranjan, Rohitash Chandra
An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis. Nat. Lang. Process. J. 4 (2023)
Rohitash Chandra, Mahir Jain, Manavendra Maharana, Pavel N. Krivitsky
Revisiting Bayesian Autoencoders With MCMC. IEEE Access 10 (2022)
Giang Ngo, Rodney Beard, Rohitash Chandra
Evolutionary bagging for ensemble learning. Neurocomputing 510 (2022)
Hodjat Shirmard, Ehsan Farahbakhsh, Elnaz Heidari, Amin Beiranvand Pour, Biswajeet Pradhan, R. Dietmar Müller, Rohitash Chandra
A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data. Remote. Sens. 14 (4) (2022)
Mingyue Kang, Seshadri Vasan, Laurence O. W. Wilson, Rohitash Chandra
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19. CoRR (2022)
Amit Krishan Kumar, M. Ritam, Lina Han, Shuli Guo, Rohitash Chandra
Deep learning for predicting respiratory rate from biosignals. Comput. Biol. Medicine 144 (2022)
Giang Ngo, Rodney Beard, Rohitash Chandra
Evolutionary bagging for ensemble learning. CoRR (2022)
Rohitash Chandra, Yash Vardhan Sharma
Surrogate-assisted distributed swarm optimisation for computationally expensive models. CoRR (2022)
Shelvin Chand, Kousik Rajesh, Rohitash Chandra
MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling Problem. CoRR (2022)
Rohitash Chandra, Animesh Tiwari
Distributed Bayesian optimisation framework for deep neuroevolution. Neurocomputing 470 (2022)
Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra
SMOTified-GAN for Class Imbalanced Pattern Classification Problems. IEEE Access 10 (2022)
Rohitash Chandra, Mukul Ranjan
Artificial intelligence for topic modelling in Hindu philosophy: mapping themes between the Upanishads and the Bhagavad Gita. CoRR (2022)
Rohitash Chandra, Venkatesh Kulkarni
Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework. IEEE Access 10 (2022)
Hardik A. Jain, Vinti Agarwal, Chaarvi Bansal, Anupama Kumar, Faheem Faheem, Muzaffar-Ur-Rehman Mohammed, Sankaranarayanan Murugesan, Moana M. Simpson, Avinash V. Karpe, Rohitash Chandra, Christopher A. MacRaild, Ian K. Styles, Amanda L. Peterson, Matthew A. Cooper, Carl M. J. Kirkpatrick, Rohan M. Shah, Enzo A. Palombo, Natalie L. Trevaskis, Darren J. Creek, Seshadri S. Vasan
CoviRx: A User-Friendly Interface for Systematic Down-Selection of Repurposed Drug Candidates for COVID-19. Data 7 (11) (2022)
Arpit Kapoor, Eshwar Nukala, Rohitash Chandra
Bayesian neuroevolution using distributed swarm optimization and tempered MCMC. Appl. Soft Comput. 129 (2022)
Rohitash Chandra, Venkatesh Kulkarni
Semantic and sentiment analysis of selected Bhagavad Gita translations using BERT-based language framework. CoRR (2022)
Animesh Renanse, Rohitash Chandra, Alok Sharma
Memory Capacity of Neural Turing Machines with Matrix Representation. CoRR (2021)
Rohitash Chandra, Ritij Saini
Biden vs Trump: Modeling US General Elections Using BERT Language Model. IEEE Access 9 (2021)
Rohitash Chandra, Aswin Krishna
COVID-19 sentiment analysis via deep learning during the rise of novel cases. CoRR (2021)
Rohitash Chandra, Ayush Bhagat, Manavendra Maharana, Pavel N. Krivitsky
Bayesian graph convolutional neural networks via tempered MCMC. CoRR (2021)
Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller
Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. Environ. Model. Softw. 139 (2021)
Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra
SMOTified-GAN for class imbalanced pattern classification problems. CoRR (2021)
Rohitash Chandra, Shaurya Goyal, Rishabh Gupta
Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction. IEEE Access 9 (2021)
Rohitash Chandra, Shaurya Goyal, Rishabh Gupta
Evaluation of deep learning models for multi-step ahead time series prediction. CoRR (2021)
Rohitash Chandra, Ayush Jain, Divyanshu Singh Chauhan
Deep learning via LSTM models for COVID-19 infection forecasting in India. CoRR (2021)
Rohitash Chandra, Mahir Jain, Manavendra Maharana, Pavel N. Krivitsky
Revisiting Bayesian Autoencoders with MCMC. CoRR (2021)
Rohitash Chandra, Ayush Bhagat, Manavendra Maharana, Pavel N. Krivitsky
Bayesian Graph Convolutional Neural Networks via Tempered MCMC. IEEE Access 9 (2021)
Animesh Tiwari, Rishabh Gupta, Rohitash Chandra
Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown. CoRR (2021)
Hodjat Shirmard, Ehsan Farahbakhsh, R. Dietmar Müller, Rohitash Chandra
A review of machine learning in processing remote sensing data for mineral exploration. CoRR (2021)
Rohitash Chandra, Konark Jain, Arpit Kapoor, Ashray Aman
Surrogate-assisted parallel tempering for Bayesian neural learning. Eng. Appl. Artif. Intell. 94 (2020)
Rohitash Chandra, Arpit Kapoor
Bayesian neural multi-source transfer learning. Neurocomputing 378 (2020)
Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Richard Scalzo, Sally Cripps
: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. Environ. Model. Softw. 125 (2020)
Ehsan Farahbakhsh, Ardeshir Hezarkhani, Taymour Eslamkish, Abbas Bahroudi, Rohitash Chandra
3DWofE: An open-source software package for three-dimensional weights of evidence modeling. Softw. Impacts 6 (2020)
Hodjat Shirmard, Ehsan Farahbakhsh, Amin Beiranvand Pour, Aidy M. Muslim, R. Dietmar Müller, Rohitash Chandra
Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data. Remote. Sens. 12 (8) (2020)
Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. Comput. Geosci. 131 (2019)
Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
Langevin-gradient parallel tempering for Bayesian neural learning. Neurocomputing 359 (2019)
Ratneel Deo, Rohitash Chandra
Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks. PRICAI (2) (2019)
Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh
Co-evolutionary multi-task learning for dynamic time series prediction. Appl. Soft Comput. 70 (2018)
Rohitash Chandra, Sally Cripps
Bayesian Multi-task Learning for Dynamic Time Series Prediction. IJCNN (2018)
Ehsan Farahbakhsh, Rohitash Chandra, Hugo K. H. Olierook, Richard Scalzo, Chris Clark, Steven M. Reddy, R. Dietmar Müller
Computer vision-based framework for extracting geological lineaments from optical remote sensing data. CoRR (2018)
Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. CoRR (2018)
Rohitash Chandra, Danial Azam, Arpit Kapoor, R. Dietmar Müller
Surrogate-assisted Bayesian inversion for landscape and basin evolution models. CoRR (2018)
Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps
Multi-core parallel tempering Bayeslands for basin and landscape evolution. CoRR (2018)
Rohitash Chandra
Multi-Task Modular Backpropagation For Dynamic Time Series Prediction. IJCNN (2018)
Rohitash Chandra, Konark Jain, Arpit Kapoor
Surrogate-assisted parallel tempering for Bayesian neural learning. CoRR (2018)
Gary Wong, Anuraganand Sharma, Rohitash Chandra
Information Collection Strategies In Memetic Cooperative Neuroevolution For Time Series Prediction. IJCNN (2018)
Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. CoRR (2018)
Rohitash Chandra, Abhishek Gupta, Yew-Soon Ong, Chi-Keong Goh
Evolutionary Multi-task Learning for Modular Knowledge Representation in Neural Networks. Neural Process. Lett. 47 (3) (2018)
Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
Langevin-gradient parallel tempering for Bayesian neural learning. CoRR (2018)
Rohitash Chandra, Sally Cripps
Coevolutionary multi-task learning for feature-based modular pattern classification. Neurocomputing 319 (2018)
Yanfei Zhang, Rohitash Chandra, Junbin Gao
Cyclone Track Prediction with Matrix Neural Networks. IJCNN (2018)
Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Sally Cripps
BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. CoRR (2018)
Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh
Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction. Neurocomputing 243 (2017)
Shonal Chaudhry, Rohitash Chandra
Face detection and recognition in an unconstrained environment for mobile visual assistive system. Appl. Soft Comput. 53 (2017)
Rohitash Chandra
Towards an Affective Computational Model for Machine Consciousness. ICONIP (5) (2017)
Rohitash Chandra
Co-evolutionary Multi-task Learning for Modular Pattern Classification. ICONIP (6) (2017)
Rohitash Chandra
Multi-task Modular Backpropagation for Feature-Based Pattern Classification. ICONIP (6) (2017)
Ratneel Vikash Deo, Rohitash Chandra, Anuraganand Sharma
Stacked transfer learning for tropical cyclone intensity prediction. CoRR (2017)
Rohitash Chandra
Towards prediction of rapid intensification in tropical cyclones with recurrent neural networks. CoRR (2017)
Rohitash Chandra
An affective computational model for machine consciousness. CoRR (2017)
Rohitash Chandra, Lamiae Azizi, Sally Cripps
Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. ICONIP (5) (2017)
Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh
Co-evolutionary multi-task learning for dynamic time series prediction. CoRR (2017)
Rohitash Chandra
Dynamic Cyclone Wind-Intensity Prediction Using Co-Evolutionary Multi-task Learning. ICONIP (5) (2017)
Shamina Hussein, Rohitash Chandra, Anuraganand Sharma
Multi-step-ahead chaotic time series prediction using coevolutionary recurrent neural networks. CEC (2016)
Ravneil Nand, Rohitash Chandra
Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction. ACALCI (2016)
Ravneil Nand, Rohitash Chandra
Competitive Island Cooperative Neuro-evolution of Feedforward Networks for Time Series Prediction. ACALCI (2016)
Mashud Rana, Rohitash Chandra, Vassilios G. Agelidis
Cooperative neuro-evolutionary recurrent neural networks for solar power prediction. CEC (2016)
Rohitash Chandra, Ratneel Deo, Christian W. Omlin
An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks. IJCNN (2016)
Rohitash Chandra, Ratneel Deo, Kavitesh Bali, Anurag Sharma
On the relationship of degree of separability with depth of evolution in decomposition for cooperative coevolution. CEC (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rohitash Chandra