Rohitash Chandra

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Citations	2662	2035
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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
Luc RollandAvailable for consultancyVerified email at uws.ac.uk
Christian OmlinUniversity of AgderVerified email at uia.no
Yew-Soon OngPresident Chair Professor of Computer Science, A*Star AI Chief ScientistVerified email at ntu.edu.sg
Ratneel DeoGraduate Computer ScientistVerified email at usp.ac.fj
Richard ScalzoCSIROVerified email at data61.csiro.au
Hugo OlierookResearch Fellow in Geology, Curtin UniversityVerified email at curtin.edu.au
Hojat ShirmardMineral exploration consultant, ParsOlang Engineering Consultant CompanyVerified email at ut.ac.ir
Danial AzamUniversity of SydneyVerified email at sydney.edu.au
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
Tristan SallesSchool of Geosciences, The University of SydneyVerified email at sydney.edu.au
Abhishek GuptaRamanujan Fellow, IIT Goa; (formerly Scientist at A*STAR and NTU Singapore)Verified email at iitgoa.ac.in
Kavitesh Kumar BaliCentre for Frontier AI Research (CFAR), A*STAR, SingaporeVerified email at cfar.a-star.edu.sg
Steven ReddyProfessor of Geology, Curtin UniversityVerified email at curtin.edu.au
Chris ClarkProfessor of Geology, Curtin UniversityVerified email at curtin.edu.au

Rohitash Chandra

UNSW

Verified email at unsw.edu.au - Homepage

Bayesian deep learning Neuroevolution MCMC NLP Mineral Exploration


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Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction R Chandra, M Zhang Neurocomputing 86, 116-123, 2012	265	2012
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	171	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	121	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	113	2021
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	105	2022
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	88	2017
COVID-19 sentiment analysis via deep learning during the rise of novel cases R Chandra, A Krishna PloS One 16 (8), e0255615, 2021	81	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	54	2016
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	52	2020
Evolutionary multi-task learning for modular training of feedforward neural networks R Chandra, A Gupta, YS Ong, CK Goh Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016	48	2016
Co-evolutionary multi-task learning for dynamic time series prediction R Chandra, YS Ong, CK Goh Applied Soft Computing 70, 576-589, 2018	47	2018
On the issue of separability for problem decomposition in cooperative neuro-evolution R Chandra, M Frean, M Zhang Neurocomputing 87, 33-40, 2012	45	2012
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	44	2018
Design of a mobile face recognition system for visually impaired persons S Chaudhry, R Chandra arXiv preprint arXiv:1502.00756, 2015	44	2015
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	42	2020
Langevin-gradient parallel tempering for Bayesian neural learning R Chandra, K Jain, RV Deo, S Cripps Neurocomputing 359, 315-326, 2019	39	2019
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	37	2021
Encoding subcomponents in cooperative co-evolutionary recurrent neural networks R Chandra, M Frean, M Zhang, CW Omlin Neurocomputing 74 (17), 3223-3234, 2011	36	2011
Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic R Chandra, Y He PloS One 16 (7), e0253217, 2021	34	2021
Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown A Tiwari, R Gupta, R Chandra arXiv preprint arXiv:2102.10551, 2021	32	2021

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