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Rohitash Chandra
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Publications
- 2024
- [j45]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: 12164-12180 (2024) - [j43]Nhat Minh Nguyen, Minh-Ngoc Tran, Rohitash Chandra:
Sequential reversible jump MCMC for dynamic Bayesian neural networks. Neurocomputing 564: 126960 (2024) - 2023
- [j41]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: 105654 (2023) - [j40]Arpit Kapoor, Sahani Pathiraja, Lucy Marshall, Rohitash Chandra:
DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling. Environ. Model. Softw. 169: 105831 (2023) - [j37]Saharsh Barve, Jody M. Webster, Rohitash Chandra:
Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing. Inf. 14(7): 373 (2023) - [i40]Saharsh Barve, Jody M. Webster, Rohitash Chandra:
Reef-insight: A framework for reef habitat mapping with clustering methods via remote sensing. CoRR abs/2301.10876 (2023) - 2022
- [j35]Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra:
SMOTified-GAN for Class Imbalanced Pattern Classification Problems. IEEE Access 10: 30655-30665 (2022) - [j33]Arpit Kapoor, Eshwar Nukala, Rohitash Chandra:
Bayesian neuroevolution using distributed swarm optimization and tempered MCMC. Appl. Soft Comput. 129: 109528 (2022) - [j28]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): 819 (2022) - 2021
- [j24]Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller:
Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. Environ. Model. Softw. 139: 105002 (2021) - [i23]Hodjat Shirmard, Ehsan Farahbakhsh, R. Dietmar Müller, Rohitash Chandra:
A review of machine learning in processing remote sensing data for mineral exploration. CoRR abs/2103.07678 (2021) - [i17]Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra:
SMOTified-GAN for class imbalanced pattern classification problems. CoRR abs/2108.03235 (2021) - 2020
- [j23]Rohitash Chandra, Konark Jain, Arpit Kapoor, Ashray Aman:
Surrogate-assisted parallel tempering for Bayesian neural learning. Eng. Appl. Artif. Intell. 94: 103700 (2020) - [j22]Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Richard Scalzo, Sally Cripps:
Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. Environ. Model. Softw. 125: 104610 (2020) - [j21]Rohitash Chandra, Arpit Kapoor:
Bayesian neural multi-source transfer learning. Neurocomputing 378: 54-64 (2020) - [j20]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): 1261 (2020) - [j19]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: 100039 (2020) - 2019
- [j18]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: 89-101 (2019) - [j17]Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps:
Langevin-gradient parallel tempering for Bayesian neural learning. Neurocomputing 359: 315-326 (2019) - [c51]Ratneel Deo, Rohitash Chandra:
Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks. PRICAI (2) 2019: 282-295 - 2018
- [j16]Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh:
Co-evolutionary multi-task learning for dynamic time series prediction. Appl. Soft Comput. 70: 576-589 (2018) - [j15]Rohitash Chandra, Sally Cripps:
Coevolutionary multi-task learning for feature-based modular pattern classification. Neurocomputing 319: 164-175 (2018) - [j14]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): 993-1009 (2018) - [c49]Rohitash Chandra, Sally Cripps:
Bayesian Multi-task Learning for Dynamic Time Series Prediction. IJCNN 2018: 1-8 - [c48]Gary Wong, Anuraganand Sharma, Rohitash Chandra:
Information Collection Strategies In Memetic Cooperative Neuroevolution For Time Series Prediction. IJCNN 2018: 1-6 - [c47]Yanfei Zhang, Rohitash Chandra, Junbin Gao:
Cyclone Track Prediction with Matrix Neural Networks. IJCNN 2018: 1-8 - [i16]Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps:
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. CoRR abs/1805.03696 (2018) - [i15]Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps:
Multi-core parallel tempering Bayeslands for basin and landscape evolution. CoRR abs/1806.10939 (2018) - [i14]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 abs/1808.02763 (2018) - [i13]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 abs/1810.02320 (2018) - [i12]Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps:
Langevin-gradient parallel tempering for Bayesian neural learning. CoRR abs/1811.04343 (2018) - [i11]Rohitash Chandra, Konark Jain, Arpit Kapoor:
Surrogate-assisted parallel tempering for Bayesian neural learning. CoRR abs/1811.08687 (2018) - [i10]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 abs/1812.00318 (2018) - [i9]Rohitash Chandra, Danial Azam, Arpit Kapoor, R. Dietmar Müller:
Surrogate-assisted Bayesian inversion for landscape and basin evolution models. CoRR abs/1812.08655 (2018) - 2017
- [j13]Shonal Chaudhry, Rohitash Chandra:
Face detection and recognition in an unconstrained environment for mobile visual assistive system. Appl. Soft Comput. 53: 168-180 (2017) - [j12]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: 21-34 (2017) - [c45]Rohitash Chandra, Lamiae Azizi, Sally Cripps:
Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. ICONIP (5) 2017: 564-573 - [i6]Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh:
Co-evolutionary multi-task learning for dynamic time series prediction. CoRR abs/1703.01887 (2017) - [i5]Ratneel Vikash Deo, Rohitash Chandra, Anuraganand Sharma:
Stacked transfer learning for tropical cyclone intensity prediction. CoRR abs/1708.06539 (2017) - 2016
- [j10]Luc Rolland, Rohitash Chandra:
The forward kinematics of the 6-6 parallel manipulator using an evolutionary algorithm based on generalized generation gap with parent-centric crossover. Robotica 34(1): 1-22 (2016) - [c41]Ravneil Nand, Rohitash Chandra:
Competitive Island Cooperative Neuro-evolution of Feedforward Networks for Time Series Prediction. ACALCI 2016: 160-170 - [c40]Ravneil Nand, Rohitash Chandra:
Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction. ACALCI 2016: 171-182 - [c39]Ravneil Nand, Rohitash Chandra:
Coevolutionary Feature Selection and Reconstruction in Neuro-Evolution for Time Series Prediction. ACALCI 2016: 285-297 - [c38]Kavitesh Bali, Rohitash Chandra, Mohammad Nabi Omidvar:
Contribution based multi-island competitive cooperative coevolution. CEC 2016: 1823-1830 - [c37]Shamina Hussein, Rohitash Chandra, Anuraganand Sharma:
Multi-step-ahead chaotic time series prediction using coevolutionary recurrent neural networks. CEC 2016: 3084-3091 - [c35]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: 4823-4830 - [c34]Shamina Hussein, Rohitash Chandra:
Chaotic Feature Selection and Reconstruction in Time Series Prediction. ICONIP (3) 2016: 3-11 - [c33]Rohitash Chandra, Abhishek Gupta, Yew-Soon Ong, Chi Keong Goh:
Evolutionary Multi-task Learning for Modular Training of Feedforward Neural Networks. ICONIP (2) 2016: 37-46 - [c32]Gary Wong, Rohitash Chandra, Anuraganand Sharma:
Memetic Cooperative Neuro-Evolution for Chaotic Time Series Prediction. ICONIP (3) 2016: 299-308 - [c31]Shonal Chaudhry, Rohitash Chandra:
Unconstrained Face Detection from a Mobile Source Using Convolutional Neural Networks. ICONIP (2) 2016: 567-576 - [c30]Ratneel Deo, Rohitash Chandra:
Identification of minimal timespan problem for recurrent neural networks with application to cyclone wind-intensity prediction. IJCNN 2016: 489-496 - [c29]Rohitash Chandra, Ratneel Deo, Christian W. Omlin:
An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks. IJCNN 2016: 4865-4872 - 2015
- [j9]Rohitash Chandra, Luc Rolland:
Global-local population memetic algorithm for solving the forward kinematics of parallel manipulators. Connect. Sci. 27(1): 22-39 (2015) - [c28]Kavitesh K. Bali, Rohitash Chandra:
Scaling up Multi-island Competitive Cooperative Coevolution for Real Parameter Global Optimisation. Australasian Conference on Artificial Intelligence 2015: 34-48 - [c27]Rohitash Chandra, Kavitesh Bali:
Competitive two-island cooperative coevolution for real parameter global optimisation. CEC 2015: 93-100 - [c25]Rohitash Chandra, Kavina Dayal:
Cooperative neuro-evolution of Elman recurrent networks for tropical cyclone wind-intensity prediction in the South Pacific region. CEC 2015: 1784-1791 - [c24]Rohitash Chandra, Kavina S. Dayal:
Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region. ICONIP (3) 2015: 43-52 - [c23]Ravneil Nand, Rohitash Chandra:
Neuron-Synapse Level Problem Decomposition Method for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction. ICONIP (3) 2015: 90-100 - [c22]Kavitesh K. Bali, Rohitash Chandra:
Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization. ICONIP (3) 2015: 127-136 - [c21]Kavitesh K. Bali, Rohitash Chandra, Mohammad Nabi Omidvar:
Competitive Island-Based Cooperative Coevolution for Efficient Optimization of Large-Scale Fully-Separable Continuous Functions. ICONIP (3) 2015: 137-147 - [c20]Gary Wong, Rohitash Chandra:
Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification. ICONIP (1) 2015: 293-301 - [c19]Rohitash Chandra, Kavina Dayal, Nicholas Rollings:
Application of cooperative neuro-evolution of Elman recurrent networks for a two-dimensional cyclone track prediction for the south pacific region. IJCNN 2015: 1-8 - [c18]Rohitash Chandra, Gary Wong:
Competitive two-island cooperative co-evolution for training feedforward neural networks for pattern classification problems. IJCNN 2015: 1-8 - [i4]Shonal Chaudhry, Rohitash Chandra:
Design of a Mobile Face Recognition System for Visually Impaired Persons. CoRR abs/1502.00756 (2015) - [i3]Daryl Abel, Bulou Gavidi, Nicholas Rollings, Rohitash Chandra:
Development of an Android Application for an Electronic Medical Record System in an Outpatient Environment for Healthcare in Fiji. CoRR abs/1503.00810 (2015) - [i2]Emmenual Reddy, Sarnil Kumar, Nicholas Rollings, Rohitash Chandra:
Mobile Application for Dengue Fever Monitoring and Tracking via GPS: Case Study for Fiji. CoRR abs/1503.00814 (2015) - 2012
- [j6]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
Crossover-based local search in cooperative co-evolutionary feedforward neural networks. Appl. Soft Comput. 12(9): 2924-2932 (2012) - [j5]Rohitash Chandra, Mengjie Zhang:
Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction. Neurocomputing 86: 116-123 (2012) - [j4]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
On the issue of separability for problem decomposition in cooperative neuro-evolution. Neurocomputing 87: 33-40 (2012) - [j3]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
Adapting modularity during learning in cooperative co-evolutionary recurrent neural networks. Soft Comput. 16(6): 1009-1020 (2012) - [c13]Rohitash Chandra, Mengjie Zhang, Lifeng Peng:
Application of Cooperative Convolution Optimization for 13C Metabolic Flux Analysis: Simulation of Isotopic Labeling Patterns Based on Tandem Mass Spectrometry Measurements. SEAL 2012: 178-187 - 2011
- [j2]Rohitash Chandra, Luc Rolland:
On solving the forward kinematics of 3RPR planar parallel manipulator using hybrid metaheuristics. Appl. Math. Comput. 217(22): 8997-9008 (2011) - [j1]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang, Christian W. Omlin:
Encoding subcomponents in cooperative co-evolutionary recurrent neural networks. Neurocomputing 74(17): 3223-3234 (2011) - [c12]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
A memetic framework for cooperative coevolution of recurrent neural networks. IJCNN 2011: 673-680 - [c11]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
Modularity adaptation in cooperative coevolution of feedforward neural networks. IJCNN 2011: 681-688 - 2010
- [c10]Rohitash Chandra, Marcus R. Frean, Mengjie Zhang:
An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural Networks. Australasian Conference on Artificial Intelligence 2010: 253-262 - 2009
- [c9]Rohitash Chandra, Marcus R. Frean, Luc Rolland:
A meta-heuristic paradigm for solving the forward kinematics of 6-6 general parallel manipulator. CIRA 2009: 171-176 - [c8]Rohitash Chandra, Mengjie Zhang, Luc Rolland:
Solving the forward kinematics of the 3RPR planar parallel manipulator using a hybrid meta-heuristic paradigm. CIRA 2009: 177-182 - [c7]Luc Rolland, Rohitash Chandra:
Forward kinematics of the 3RPR planar parallel manipulators using real coded genetic algorithms. ISCIS 2009: 381-386 - 2008
- [c6]Rohitash Chandra, Christian W. Omlin:
Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent Neural Networks. GEM 2008: 305-311 - 2007
- [c5]Rohitash Chandra, Christian W. Omlin:
A Hybrid Recurrent Neural Networks Architecture Inspired by Hidden Markov Models: Training and Extraction of Deterministic Finite Automaton. Artificial Intelligence and Pattern Recognition 2007: 278-285 - [c4]Rohitash Chandra, Christian W. Omlin:
The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification. Artificial Intelligence and Pattern Recognition 2007: 286-293 - [c3]Rohitash Chandra, Christian W. Omlin:
Knowledge Discovery using Artificial Neural Networks for a Conservation Biology Domain. DMIN 2007: 221-227 - [c2]Rohitash Chandra, Christian W. Omlin:
Hybrid Recurrent Neural Networks: An Application to Phoneme Classification. GEM 2007: 57-62 - 2006
- [c1]Rohitash Chandra, Christian W. Omlin:
Training and extraction of fuzzy finite state automata in recurrent neural networks. Computational Intelligence 2006: 274-279
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