Select Publications

Book Chapters

Deo R; Chandra R, 2019, 'Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks', in , pp. 282 - 295,

Chandra R; Azizi L; Cripps S, 2017, 'Bayesian neural learning via langevin dynamics for chaotic time series prediction', in , pp. 564 - 573,

Chandra R, 2017, 'Co-evolutionary multi-task learning for modular pattern classification', in , pp. 692 - 701,

Chandra R, 2017, 'Dynamic cyclone wind-intensity prediction using co-evolutionary multi-task learning', in , pp. 618 - 627,

Chandra R, 2017, 'Multi-task modular backpropagation for feature-based pattern classification', in , pp. 558 - 566,

Chandra R, 2017, 'Towards an affective computational model for machine consciousness', in , pp. 897 - 907,

Hussein S; Chandra R, 2016, 'Chaotic feature selection and reconstruction in time series prediction', in , pp. 3 - 11,

Nand R; Chandra R, 2016, 'Coevolutionary feature selection and reconstruction in neuro-evolution for time series prediction', in , pp. 285 - 297,

Nand R; Chandra R, 2016, 'Competitive Island cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 160 - 170,

Chandra R; Gupta A; Ong YS; Goh CK, 2016, 'Evolutionary multi-task learning for modular training of feedforward neural networks', in , pp. 37 - 46,

Wong G; Chandra R; Sharma A, 2016, 'Memetic cooperative neuro-evolution for chaotic time series prediction', in , pp. 299 - 308,

Nand R; Chandra R, 2016, 'Reverse neuron level decomposition for cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 171 - 182,

Chaudhry S; Chandra R, 2016, 'Unconstrained face detection from a mobile source using convolutional neural networks', in , pp. 567 - 576,

Chandra R; Dayal KS, 2015, 'Coevolutionary recurrent neural networks for prediction of rapid intensification in wind intensity of tropical cyclones in the south pacific region', in , pp. 43 - 52,

Bali KK; Chandra R; Omidvar MN, 2015, 'Competitive island-based cooperative coevolution for efficient optimization of large-scale fully-separable continuous functions', in , pp. 137 - 147,

Wong G; Chandra R, 2015, 'Enhancing competitive island cooperative neuro-evolution through backpropagation for pattern classification', in , pp. 293 - 301,

Bali KK; Chandra R, 2015, 'Multi-island competitive cooperative coevolution for real parameter global optimization', in , pp. 127 - 136,

Nand R; Chandra R, 2015, 'Neuron-synapse level problem decomposition method for cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 90 - 100,

Bali KK; Chandra R, 2015, 'Scaling up multi-island competitive cooperative coevolution for real parameter global optimisation', in , pp. 34 - 48,

Chandra R; Zhang M; Peng L, 2012, 'Application of cooperative convolution optimization for 13C metabolic flux analysis: Simulation of isotopic labeling patterns based on tandem mass spectrometry measurements', in , pp. 178 - 187,

Chandra R; Frean M; Zhang M, 2010, 'An encoding scheme for cooperative coevolutionary feedforward neural networks', in , pp. 253 - 262,

Chandra R; Zhang M; Rolland L, 2009, 'Solving the forward kinematics of the 3RPR planar parallel manipulator using a hybrid meta-heuristic paradigm', in Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA, pp. 177 - 182,

Journal articles

Bansal C; Deepa PR; Agarwal V; Chandra R, 2024, 'A clustering and graph deep learning-based framework for COVID-19 drug repurposing', Expert Systems with Applications, 249,

Chen E; Andersen MS; Chandra R, 2024, 'Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels', Environmental Modelling and Software, 178,

Khan AA; Chaudhari O; Chandra R, 2024, 'A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation', Expert Systems with Applications, 244,

Ke Y; Bian R; Chandra R, 2024, 'A unified machine learning framework for basketball team roster construction: NBA and WNBA[Formula presented]', Applied Soft Computing, 153,

Nguyen NM; Tran MN; Chandra R, 2024, 'Sequential reversible jump MCMC for dynamic Bayesian neural networks', Neurocomputing, 564,

Khan AA; Hussain S; Chandra R, 2024, 'A Quantum-Inspired Predator–Prey Algorithm for Real-Parameter Optimization', Algorithms, 17,

Chandra R; Simmons J, 2024, 'Bayesian Neural Networks via MCMC: A Python-Based Tutorial', IEEE Access, 12, pp. 70519 - 70549,

Chandra R; Tiwari A; Jain N; Badhe S, 2024, 'Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon on the Mount', IEEE Access, 12, pp. 84452 - 84469,

Deo R; Webster JM; Salles T; Chandra R, 2024, 'ReefCoreSeg: A Clustering-Based Framework for Multi-Source Data Fusion for Segmentation of Reef Drill Cores', IEEE Access, 12, pp. 12164 - 12180,

Renanse A; Sharma A; Chandra R, 2023, 'Memory capacity of recurrent neural networks with matrix representation', Neurocomputing, 560,

Chandra R; Sharma YV, 2023, 'Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models', Computational Geosciences, 27, pp. 939 - 954,

Bai G; Chandra R, 2023, 'Gradient boosting Bayesian neural networks via Langevin MCMC', Neurocomputing, 558,

Kapoor A; Pathiraja S; Marshall L; Chandra R, 2023, 'DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling', Environmental Modelling and Software, 169,

Lande J; Pillay A; Chandra R, 2023, 'Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron', PLoS ONE, 18,

Barve S; Webster JM; Chandra R, 2023, 'Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing', Information (Switzerland), 14,

Chandra R; Bansal C; Kang M; Blau T; Agarwal V; Singh P; Wilson LOW; Vasan S, 2023, 'Unsupervised machine learning framework for discriminating major variants of concern during COVID-19', PLoS ONE, 18,

Kapoor A; Negi A; Marshall L; Chandra R, 2023, 'Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks', Environmental Modelling and Software, 162,

Kumar AK; Jain S; Jain S; Ritam M; Xia Y; Chandra R, 2023, 'Physics-informed neural entangled-ladder network for inhalation impedance of the respiratory system', Computer Methods and Programs in Biomedicine, 231,

Shukla A; Bansal C; Badhe S; Ranjan M; Chandra R, 2023, 'An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis', Natural Language Processing Journal, 4, pp. 100025 - 100025,

Kapoor A; Nukala E; Chandra R, 2022, 'Bayesian neuroevolution using distributed swarm optimization and tempered MCMC[Formula presented]', Applied Soft Computing, 129,

Jain HA; Agarwal V; Bansal C; Kumar A; Faheem ; Mohammed MUR; Murugesan S; Simpson MM; Karpe AV; Chandra R; MacRaild CA; Styles IK; Peterson AL; Cooper MA; Kirkpatrick CMJ; Shah RM; Palombo EA; Trevaskis NL; Creek DJ; Vasan SS, 2022, 'CoviRx: A User-Friendly Interface for Systematic Down-Selection of Repurposed Drug Candidates for COVID-19', Data, 7,

Ngo G; Beard R; Chandra R, 2022, 'Evolutionary bagging for ensemble learning', Neurocomputing, 510, pp. 1 - 14,

Anshuka A; Chandra R; Buzacott AJV; Sanderson D; van Ogtrop FF, 2022, 'Spatio temporal hydrological extreme forecasting framework using LSTM deep learning model', Stochastic Environmental Research and Risk Assessment, 36, pp. 3467 - 3485,

Chandra R; Ranjan M, 2022, 'Artificial intelligence for topic modelling in Hindu philosophy: Mapping themes between the Upanishads and the Bhagavad Gita', PLoS ONE, 17,

Kumar AK; Ritam M; Han L; Guo S; Chandra R, 2022, 'Deep learning for predicting respiratory rate from biosignals', Computers in Biology and Medicine, 144,

Shirmard H; Farahbakhsh E; Heidari E; Pour AB; Pradhan B; Müller D; Chandra R, 2022, 'A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data', Remote Sensing, 14,

Chandra R; Tiwari A, 2022, 'Distributed Bayesian optimisation framework for deep neuroevolution', Neurocomputing, 470, pp. 51 - 65,

Shirmard H; Farahbakhsh E; Müller RD; Chandra R, 2022, 'A review of machine learning in processing remote sensing data for mineral exploration', Remote Sensing of Environment, 268,

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