Rohitash Chandra

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Mengjie Zhang，FRSNZ, FEngNZ, FIE...Professor of Computer Science, Victoria University of WellingtonVerified email at ecs.vuw.ac.nz
Ehsan FarahbakhshEarthByte Group, School of Geosciences, University of SydneyVerified email at sydney.edu.au
Dietmar MüllerProfessor of Geophysics, EarthByte Group, Univ. of SydneyVerified email at sydney.edu.au
Marcus FreanVictoria University of WellingtonVerified email at ecs.vuw.ac.nz
Sally (Wood) CrippsUniversity of Technology SydneyVerified email at uts.edu.au
Ratneel DeoPost Doctoral ResearcherVerified email at sydney.edu.au
Luc RollandAvailable for consultancyVerified email at uws.ac.uk
Christian OmlinUniversity of Agder, NorwayVerified email at uia.no
Yew-Soon OngPresident Chair Professor of Computer Science, A*Star AI Chief Scientist, FIEEEVerified email at ntu.edu.sg
Richard ScalzoCSIROVerified email at data61.csiro.au
Hojat ShirmardPhD Candidate at the University of SydneyVerified email at ut.ac.ir
Arpit KapoorPhD Candidate, UNSW SydneyVerified email at unsw.edu.au
Dr. Anuraganand SharmaThe University of the South Pacific, Fiji and University of Canberra, AustraliaVerified email at usp.ac.fj
Hugo OlierookSenior Research Fellow in Geology, Curtin UniversityVerified email at curtin.edu.au
Tristan SallesSchool of Geosciences, The University of SydneyVerified email at sydney.edu.au
Steven ReddyProfessor of Geology, Curtin UniversityVerified email at curtin.edu.au
Chris ClarkProfessor of Geology, Curtin UniversityVerified email at curtin.edu.au
Danial AzamUniversity of SydneyVerified email at sydney.edu.au
Rodney BeardPingla InstituteVerified email at athabascau.ca
Jody M. WebsterProfessor of Marine Geoscience, Geocoastal Research Group, School of Geosciences, University ofVerified email at sydney.edu.au

Rohitash Chandra

UNSW

Verified email at unsw.edu.au - Homepage

Bayesian deep learning Neuroevolution Climate Extremes Language Models Comparative Religion


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction R Chandra, M Zhang Neurocomputing 86, 116-123, 2012	287	2012
A review of machine learning in processing remote sensing data for mineral exploration H Shirmard, E Farahbakhsh, D Muller, R Chandra Remote Sensing of Environment 268, 112750, 2022	266	2022
Evaluation of deep learning models for multi-step ahead time series prediction R Chandra, S Goyal, R Gupta IEEE Access 9, 83105-83123, 2021	200	2021
Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction R Chandra IEEE Transactions on Neural Networks and Learning Systems, 2015	189	2015
Deep learning via LSTM models for COVID-19 infection forecasting in India R Chandra, A Jain, DS Chauhan PLOS One 17 (1), e0262708, 2022	176	2022
COVID-19 sentiment analysis via deep learning during the rise of novel cases R Chandra, A Krishna PloS One 16 (8), e0255615, 2021	137	2021
Evolutionary bagging for ensemble learning G Ngo, R Beard, R Chandra Neurocomputing, 2022	123	2022
A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation AA Khan, O Chaudhari, R Chandra Expert Systems with Applications, 2024	122	2024
Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction R Chandra, YS Ong, CK Goh Neurocomputing 243, 21-34, 2017	95	2017
SMOTified-GAN for class imbalanced pattern classification problems A Sharma, PK Singh, R Chandra IEEE Access, 2022	92	2022
Deep learning for predicting respiratory rate from biosignals AK Kumar, M Ritam, L Han, S Guo, R Chandra Computers in biology and medicine 144, 105338, 2022	71	2022
Integration of selective dimensionality reduction techniques for mineral exploration using ASTER satellite data H Shirmard, E Farahbakhsh, A Beiranvand Pour, AM Muslim, RD Müller, ... Remote Sensing 12 (8), 1261, 2020	68	2020
Computer vision-based framework for extracting geological lineaments from optical remote sensing data E Farahbakhsh, R Chandra, HKH Olierook, R Scalzo, C Clark, SM Reddy, ... International Journal of Remote Sensing, 2020	66	2020
A comparative study of convolutional neural networks and conventional machine learning models for lithological mapping using remote sensing data H Shirmard, E Farahbakhsh, E Heidari, A Beiranvand Pour, B Pradhan, ... Remote Sensing 14 (4), 819, 2022	62	2022
Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models HKH Olierook, R Scalzo, D Kohn, R Chandra, E Farahbakhsh, ... Geoscience Frontiers, 2021	62	2021
Evaluation of co-evolutionary neural network architectures for time series prediction with mobile application in finance R Chandra, S Chand Applied Soft Computing 49, 462-473, 2016	61	2016
Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic R Chandra, Y He PloS One 16 (7), e0253217, 2021	58	2021
Mobile application for dengue fever monitoring and tracking via GPS: case study for Fiji E Reddy, S Kumar, N Rollings, R Chandra arXiv preprint arXiv:1503.00814, 2015	58	2015
Co-evolutionary multi-task learning for dynamic time series prediction R Chandra, YS Ong, CK Goh Applied Soft Computing 70, 576-589, 2018	53	2018
Evolutionary multi-task learning for modular knowledge representation in neural networks R Chandra, A Gupta, YS Ong, CK Goh Neural Processing Letters 47 (3), 993-1009, 2018	50	2018

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