Training and extraction of fuzzy finite state automata in recurrent neural networks. - Rohitash Chandra; Christian W. Omlin (Computational Intelligence, 2006)

A Hybrid Recurrent Neural Networks Architecture Inspired by Hidden Markov Models: Training and Extraction of Deterministic Finite Automaton. - Rohitash Chandra; Christian W. Omlin (Artificial Intelligence and Pattern Recognition, 2007)

The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification. - Rohitash Chandra; Christian W. Omlin (Artificial Intelligence and Pattern Recognition, 2007)

Knowledge Discovery using Artificial Neural Networks for a Conservation Biology Domain. - Rohitash Chandra; Christian W. Omlin (DMIN, 2007)

Hybrid Recurrent Neural Networks: An Application to Phoneme Classification. - Rohitash Chandra; Christian W. Omlin (GEM, 2007)

Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent Neural Networks. - Rohitash Chandra; Christian W. Omlin (GEM, 2008)

A meta-heuristic paradigm for solving the forward kinematics of 6-6 general parallel manipulator. - Rohitash Chandra; Marcus R. Frean; Luc Rolland (CIRA, 2009)

Solving the forward kinematics of the 3RPR planar parallel manipulator using a hybrid meta-heuristic paradigm. - Rohitash Chandra; Mengjie Zhang 001; Luc Rolland (CIRA, 2009)

Forward kinematics of the 3RPR planar parallel manipulators using real coded genetic algorithms. - Luc Rolland; Rohitash Chandra (ISCIS, 2009)

An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural Networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (Australasian Conference on Artificial Intelligence, 2010)

A memetic framework for cooperative coevolution of recurrent neural networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (IJCNN, 2011)

Modularity adaptation in cooperative coevolution of feedforward neural networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (IJCNN, 2011)

On solving the forward kinematics of 3RPR planar parallel manipulator using hybrid metaheuristics. - Rohitash Chandra; Luc Rolland (Appl. Math. Comput., 2011)

Encoding subcomponents in cooperative co-evolutionary recurrent neural networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001; Christian W. Omlin (Neurocomputing, 2011)

Application of Cooperative Convolution Optimization for 13C Metabolic Flux Analysis: Simulation of Isotopic Labeling Patterns Based on Tandem Mass Spectrometry Measurements. - Rohitash Chandra; Mengjie Zhang 001; Lifeng Peng (SEAL, 2012)

Crossover-based local search in cooperative co-evolutionary feedforward neural networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (Appl. Soft Comput., 2012)

On the issue of separability for problem decomposition in cooperative neuro-evolution. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (Neurocomputing, 2012)

Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction. - Rohitash Chandra; Mengjie Zhang 001 (Neurocomputing, 2012)

Adapting modularity during learning in cooperative co-evolutionary recurrent neural networks. - Rohitash Chandra; Marcus R. Frean; Mengjie Zhang 001 (Soft Comput., 2012)

Problem Decomposition and Adaptation in Cooperative Neuro-Evolution. - Rohitash Chandra (2012)

Adaptive problem decomposition in cooperative coevolution of recurrent networks for time series prediction. - Rohitash Chandra (IJCNN, 2013)

Multi-objective cooperative coevolution of neural networks for time series prediction. - Shelvin Chand; Rohitash Chandra (IJCNN, 2014)

Cooperative coevolution of feed forward neural networks for financial time series problem. - Shelvin Chand; Rohitash Chandra (IJCNN, 2014)

Competitive two-island cooperative coevolution for training Elman recurrent networks for time series prediction. - Rohitash Chandra (IJCNN, 2014)

Memetic cooperative coevolution of Elman recurrent neural networks. - Rohitash Chandra (Soft Comput., 2014)

Scaling up Multi-island Competitive Cooperative Coevolution for Real Parameter Global Optimisation. - Kavitesh K. Bali; Rohitash Chandra (Australasian Conference on Artificial Intelligence, 2015)

Multi-objective cooperative neuro-evolution of recurrent neural networks for time series prediction. - Rohitash Chandra (CEC, 2015)

Competitive two-island cooperative coevolution for real parameter global optimisation. - Rohitash Chandra; Kavitesh Bali (CEC, 2015)

Cooperative neuro-evolution of Elman recurrent networks for tropical cyclone wind-intensity prediction in the South Pacific region. - Rohitash Chandra; Kavina Dayal (CEC, 2015)

Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization. - Kavitesh K. Bali; Rohitash Chandra (ICONIP (3), 2015)

Competitive Island-Based Cooperative Coevolution for Efficient Optimization of Large-Scale Fully-Separable Continuous Functions. - Kavitesh K. Bali; Rohitash Chandra; Mohammad Nabi Omidvar (ICONIP (3), 2015)

Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region. - Rohitash Chandra; Kavina S. Dayal (ICONIP (3), 2015)

Neuron-Synapse Level Problem Decomposition Method for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction. - Ravneil Nand; Rohitash Chandra (ICONIP (3), 2015)

Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification. - Gary Wong; Rohitash Chandra (ICONIP (1), 2015)

Application of cooperative neuro-evolution of Elman recurrent networks for a two-dimensional cyclone track prediction for the south pacific region. - Rohitash Chandra; Kavina Dayal; Nicholas Rollings (IJCNN, 2015)

Competitive two-island cooperative co-evolution for training feedforward neural networks for pattern classification problems. - Rohitash Chandra; Gary Wong (IJCNN, 2015)

Global-local population memetic algorithm for solving the forward kinematics of parallel manipulators. - Rohitash Chandra; Luc Rolland (Connect. Sci., 2015)

Development of an Android Application for an Electronic Medical Record System in an Outpatient Environment for Healthcare in Fiji. - Daryl Abel; Bulou Gavidi; Nicholas Rollings; Rohitash Chandra (CoRR, 2015)

Design of a Mobile Face Recognition System for Visually Impaired Persons. - Shonal Chaudhry; Rohitash Chandra (CoRR, 2015)

A Study of the Management of Electronic Medical Records in Fijian Hospitals. - Swaran S. Ravindra; Rohitash Chandra; Virallikattur S. Dhenesh (CoRR, 2015)

Mobile Application for Dengue Fever Monitoring and Tracking via GPS: Case Study for Fiji. - Emmenual Reddy; Sarnil Kumar; Nicholas Rollings; Rohitash Chandra (CoRR, 2015)

Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction. - Rohitash Chandra (IEEE Trans. Neural Networks Learn. Syst., 2015)

Competitive Island Cooperative Neuro-evolution of Feedforward Networks for Time Series Prediction. - Ravneil Nand; Rohitash Chandra (ACALCI, 2016)

Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction. - Ravneil Nand; Rohitash Chandra (ACALCI, 2016)

Coevolutionary Feature Selection and Reconstruction in Neuro-Evolution for Time Series Prediction. - Ravneil Nand; Rohitash Chandra (ACALCI, 2016)

Contribution based multi-island competitive cooperative coevolution. - Kavitesh Bali; Rohitash Chandra; Mohammad Nabi Omidvar (CEC, 2016)

On the relationship of degree of separability with depth of evolution in decomposition for cooperative coevolution. - Rohitash Chandra; Ratneel Deo; Kavitesh Bali; Anurag Sharma (CEC, 2016)

Multi-step-ahead chaotic time series prediction using coevolutionary recurrent neural networks. - Shamina Hussein; Rohitash Chandra; Anuraganand Sharma (CEC, 2016)

Cooperative neuro-evolutionary recurrent neural networks for solar power prediction. - Mashud Rana; Rohitash Chandra; Vassilios G. Agelidis (CEC, 2016)

Evolutionary Multi-task Learning for Modular Training of Feedforward Neural Networks. - Rohitash Chandra; Abhishek Gupta 001; Yew-Soon Ong; Chi Keong Goh (ICONIP (2), 2016)

Unconstrained Face Detection from a Mobile Source Using Convolutional Neural Networks. - Shonal Chaudhry; Rohitash Chandra (ICONIP (2), 2016)

Chaotic Feature Selection and Reconstruction in Time Series Prediction. - Shamina Hussein; Rohitash Chandra (ICONIP (3), 2016)

Memetic Cooperative Neuro-Evolution for Chaotic Time Series Prediction. - Gary Wong; Rohitash Chandra; Anuraganand Sharma (ICONIP (3), 2016)

An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks. - Rohitash Chandra; Ratneel Deo; Christian W. Omlin (IJCNN, 2016)

Identification of minimal timespan problem for recurrent neural networks with application to cyclone wind-intensity prediction. - Ratneel Deo; Rohitash Chandra (IJCNN, 2016)

Evaluation of co-evolutionary neural network architectures for time series prediction with mobile application in finance. - Rohitash Chandra; Shelvin Chand (Appl. Soft Comput., 2016)

The forward kinematics of the 6-6 parallel manipulator using an evolutionary algorithm based on generalized generation gap with parent-centric crossover. - Luc Rolland; Rohitash Chandra (Robotica, 2016)

Dynamic Cyclone Wind-Intensity Prediction Using Co-Evolutionary Multi-task Learning. - Rohitash Chandra (ICONIP (5), 2017)

Towards an Affective Computational Model for Machine Consciousness. - Rohitash Chandra (ICONIP (5), 2017)

Multi-task Modular Backpropagation for Feature-Based Pattern Classification. - Rohitash Chandra (ICONIP (6), 2017)

Co-evolutionary Multi-task Learning for Modular Pattern Classification. - Rohitash Chandra (ICONIP (6), 2017)

Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. - Rohitash Chandra; Lamiae Azizi; Sally Cripps (ICONIP (5), 2017)

Face detection and recognition in an unconstrained environment for mobile visual assistive system. - Shonal Chaudhry; Rohitash Chandra (Appl. Soft Comput., 2017)

An affective computational model for machine consciousness. - Rohitash Chandra (CoRR, 2017)

Towards prediction of rapid intensification in tropical cyclones with recurrent neural networks. - Rohitash Chandra (CoRR, 2017)

Stacked transfer learning for tropical cyclone intensity prediction. - Ratneel Vikash Deo; Rohitash Chandra; Anuraganand Sharma (CoRR, 2017)

Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction. - Rohitash Chandra; Yew-Soon Ong; Chi-Keong Goh (Neurocomputing, 2017)

Multi-Task Modular Backpropagation For Dynamic Time Series Prediction. - Rohitash Chandra (IJCNN, 2018)

Bayesian Multi-task Learning for Dynamic Time Series Prediction. - Rohitash Chandra; Sally Cripps (IJCNN, 2018)

Information Collection Strategies In Memetic Cooperative Neuroevolution For Time Series Prediction. - Gary Wong; Anuraganand Sharma; Rohitash Chandra (IJCNN, 2018)

Cyclone Track Prediction with Matrix Neural Networks. - Yanfei Zhang; Rohitash Chandra; Junbin Gao (IJCNN, 2018)

Co-evolutionary multi-task learning for dynamic time series prediction. - Rohitash Chandra; Yew-Soon Ong; Chi-Keong Goh (Appl. Soft Comput., 2018)

Multi-core parallel tempering Bayeslands for basin and landscape evolution. - Rohitash Chandra; R. Dietmar Müller; Ratneel Deo; Nathaniel Butterworth; Tristan Salles; Sally Cripps (CoRR, 2018)

BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. - Jodie Pall; Rohitash Chandra; Danial Azam; Tristan Salles; Jody M. Webster; Sally Cripps (CoRR, 2018)

Computer vision-based framework for extracting geological lineaments from optical remote sensing data. - Ehsan Farahbakhsh; Rohitash Chandra; Hugo K. H. Olierook; Richard Scalzo; Chris Clark; Steven M. Reddy; R. Dietmar Müller (CoRR, 2018)

Surrogate-assisted parallel tempering for Bayesian neural learning. - Rohitash Chandra; Konark Jain; Arpit Kapoor (CoRR, 2018)

Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. - Richard Scalzo; David Kohn; Hugo K. H. Olierook; Gregory Houseman; Rohitash Chandra; Mark A. Girolami; Sally Cripps (CoRR, 2018)

Surrogate-assisted Bayesian inversion for landscape and basin evolution models. - Rohitash Chandra; Danial Azam; Arpit Kapoor; R. Dietmar Müller (CoRR, 2018)

Coevolutionary multi-task learning for feature-based modular pattern classification. - Rohitash Chandra; Sally Cripps (Neurocomputing, 2018)

Evolutionary Multi-task Learning for Modular Knowledge Representation in Neural Networks. - Rohitash Chandra; Abhishek Gupta 001; Yew-Soon Ong; Chi-Keong Goh (Neural Process. Lett., 2018)

Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks. - Ratneel Deo; Rohitash Chandra (PRICAI (2), 2019)

Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. - Rohitash Chandra; Danial Azam; R. Dietmar Müller; Tristan Salles; Sally Cripps (Comput. Geosci., 2019)

Langevin-gradient parallel tempering for Bayesian neural learning. - Rohitash Chandra; Konark Jain; Ratneel Vikash Deo; Sally Cripps (Neurocomputing, 2019)

Surrogate-assisted parallel tempering for Bayesian neural learning. - Rohitash Chandra; Konark Jain; Arpit Kapoor; Ashray Aman (Eng. Appl. Artif. Intell., 2020)

Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. - Jodie Pall; Rohitash Chandra; Danial Azam; Tristan Salles; Jody M. Webster; Richard Scalzo; Sally Cripps (Environ. Model. Softw., 2020)

Bayesian neural multi-source transfer learning. - Rohitash Chandra; Arpit Kapoor (Neurocomputing, 2020)

Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data. - Hodjat Shirmard; Ehsan Farahbakhsh; Amin Beiranvand Pour; Aidy M. Muslim; R. Dietmar Müller; Rohitash Chandra (Remote. Sens., 2020)

3DWofE: An open-source software package for three-dimensional weights of evidence modeling. - Ehsan Farahbakhsh; Ardeshir Hezarkhani; Taymour Eslamkish; Abbas Bahroudi; Rohitash Chandra (Softw. Impacts, 2020)

Bayesian Graph Convolutional Neural Networks via Tempered MCMC. - Rohitash Chandra; Ayush Bhagat; Manavendra Maharana; Pavel N. Krivitsky (IEEE Access, 2021)

Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction. - Rohitash Chandra; Shaurya Goyal; Rishabh Gupta (IEEE Access, 2021)

Biden vs Trump: Modeling US General Elections Using BERT Language Model. - Rohitash Chandra; Ritij Saini (IEEE Access, 2021)

Deep learning via LSTM models for COVID-19 infection forecasting in India. - Rohitash Chandra; Ayush Jain; Divyanshu Singh Chauhan (CoRR, 2021)

Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown. - Animesh Tiwari; Rishabh Gupta; Rohitash Chandra (CoRR, 2021)

A review of machine learning in processing remote sensing data for mineral exploration. - Hodjat Shirmard; Ehsan Farahbakhsh; R. Dietmar Müller; Rohitash Chandra (CoRR, 2021)

Memory Capacity of Neural Turing Machines with Matrix Representation. - Animesh Renanse; Rohitash Chandra; Alok Sharma (CoRR, 2021)

COVID-19 sentiment analysis via deep learning during the rise of novel cases. - Rohitash Chandra; Aswin Krishna (CoRR, 2021)

Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. - Rohitash Chandra; Sally Cripps; Nathaniel Butterworth; R. Dietmar Müller (Environ. Model. Softw., 2021)

Revisiting Bayesian Autoencoders With MCMC. - Rohitash Chandra; Mahir Jain; Manavendra Maharana; Pavel N. Krivitsky (IEEE Access, 2022)

Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework. - Rohitash Chandra; Venkatesh Kulkarni (IEEE Access, 2022)

SMOTified-GAN for Class Imbalanced Pattern Classification Problems. - Anuraganand Sharma; Prabhat Kumar Singh; Rohitash Chandra (IEEE Access, 2022)

Bayesian neuroevolution using distributed swarm optimization and tempered MCMC. - Arpit Kapoor; Eshwar Nukala; Rohitash Chandra (Appl. Soft Comput., 2022)

Deep learning for predicting respiratory rate from biosignals. - Amit Krishan Kumar; M. Ritam; Lina Han; Shuli Guo; Rohitash Chandra (Comput. Biol. Medicine, 2022)

Surrogate-assisted distributed swarm optimisation for computationally expensive models. - Rohitash Chandra; Yash Vardhan Sharma (CoRR, 2022)

MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling Problem. - Shelvin Chand; Kousik Rajesh; Rohitash Chandra (CoRR, 2022)

Artificial intelligence for topic modelling in Hindu philosophy: mapping themes between the Upanishads and the Bhagavad Gita. - Rohitash Chandra; Mukul Ranjan (CoRR, 2022)

Unsupervised machine learning framework for discriminating major variants of concern during COVID-19. - Mingyue Kang; Seshadri Vasan; Laurence O. W. Wilson; Rohitash Chandra (CoRR, 2022)

CoviRx: A User-Friendly Interface for Systematic Down-Selection of Repurposed Drug Candidates for COVID-19. - 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; et al. (Data, 2022)

Distributed Bayesian optimisation framework for deep neuroevolution. - Rohitash Chandra; Animesh Tiwari (Neurocomputing, 2022)

Evolutionary bagging for ensemble learning. - Giang Ngo; Rodney Beard; Rohitash Chandra (Neurocomputing, 2022)

A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data. - Hodjat Shirmard; Ehsan Farahbakhsh; Elnaz Heidari; Amin Beiranvand Pour; Biswajeet Pradhan; R. Dietmar Müller; Rohitash Chandra (Remote. Sens., 2022)

Reef-insight: A framework for reef habitat mapping with clustering methods via remote sensing. - Saharsh Barve; Jody M. Webster; Rohitash Chandra (CoRR, 2023)

Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron. - Janhavi Lande; Arti Pillay; Rohitash Chandra (CoRR, 2023)

Bayesian neural networks via MCMC: a Python-based tutorial. - Rohitash Chandra; Royce Chen; Joshua A. Simmons (CoRR, 2023)

An analysis of vaccine-related sentiments from development to deployment of COVID-19 vaccines. - Rohitash Chandra; Jayesh Sonawane; Janhavi Lande; Cathy Yu (CoRR, 2023)

Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing. - Saharsh Barve; Jody M. Webster; Rohitash Chandra (Inf., 2023)

An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis. - Akshat Shukla; Chaarvi Bansal; Sushrut Badhe; Mukul Ranjan; Rohitash Chandra (Nat. Lang. Process. J., 2023)

Physics-informed neural entangled-ladder network for inhalation impedance of the respiratory system. - Amit Krishan Kumar; Snigdha Jain; Shirin Jain; M. Ritam; Yuanqing Xia; Rohitash Chandra (Comput. Methods Programs Biomed., 2023)

Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks. - Arpit Kapoor; Anshul Negi; Lucy A. Marshall; Rohitash Chandra (Environ. Model. Softw., 2023)

DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling. - Arpit Kapoor; Sahani Pathiraja; Lucy A. Marshall; Rohitash Chandra (Environ. Model. Softw., 2023)

Gradient boosting Bayesian neural networks via Langevin MCMC. - George Bai; Rohitash Chandra (Neurocomputing, 2023)

Memory capacity of recurrent neural networks with matrix representation. - Animesh Renanse; Alok Sharma; Rohitash Chandra (Neurocomputing, 2023)

Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. - Honghui Wang; Weiming Zhi; Gustavo Batista; Rohitash Chandra (ICRA, 2024)

Bayesian Neural Networks via MCMC: A Python-Based Tutorial. - Rohitash Chandra; Joshua A. Simmons (IEEE Access, 2024)

Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon on the Mount. - Rohitash Chandra; Abhishek Tiwari; Naman Jain; Sushrut Badhe (IEEE Access, 2024)

ReefCoreSeg: A Clustering-Based Framework for Multi-Source Data Fusion for Segmentation of Reef Drill Cores. - Ratneel Deo; Jody M. Webster; Tristan Salles; Rohitash Chandra (IEEE Access, 2024)

Recursive Deep Learning Framework for Forecasting the Decadal World Economic Outlook. - Tianyi Wang; Rodney Beard; John Hawkins; Rohitash Chandra (IEEE Access, 2024)

A Quantum-Inspired Predator-Prey Algorithm for Real-Parameter Optimization. - Azal Ahmad Khan; Salman Hussain; Rohitash Chandra (Algorithms, 2024)

A unified machine learning framework for basketball team roster construction: NBA and WNBA. - Yuhao Ke; Ranran Bian; Rohitash Chandra (Appl. Soft Comput., 2024)

An Analysis of Vaccine-Related Sentiments on Twitter (X) from Development to Deployment of COVID-19 Vaccines. - Rohitash Chandra; Jayesh Sonawane; Jahnavi Lande (Big Data Cogn. Comput., 2024)

Large language model for Bible sentiment analysis: Sermon on the Mount. - Mahek Vora; Tom Blau; Vansh Kachhwal; Ashu M. G. Solo; Rohitash Chandra (CoRR, 2024)

Self-supervised learning for skin cancer diagnosis with limited training data. - Hamish Haggerty; Rohitash Chandra (CoRR, 2024)

Remote sensing framework for geological mapping via stacked autoencoders and clustering. - Sandeep Nagar; Ehsan Farahbakhsh; Joseph L. Awange; Rohitash Chandra (CoRR, 2024)

Large language models for sentiment analysis of newspaper articles during COVID-19: The Guardian. - Rohitash Chandra; Baicheng Zhu; Qingying Fang; Eka Shinjikashvili (CoRR, 2024)

Evaluation of deep learning models for Australian climate extremes: prediction of streamflow and floods. - Siddharth Khedkar; R. Willem Vervoort; Rohitash Chandra (CoRR, 2024)

A longitudinal sentiment analysis of Sinophobia during COVID-19 using large language models. - Chen Wang; Rohitash Chandra (CoRR, 2024)

Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysis. - Xuechun Wang; Rodney Beard; Rohitash Chandra (CoRR, 2024)

Bayes-CATSI: A variational Bayesian deep learning framework for medical time series data imputation. - Omkar Kulkarni; Rohitash Chandra (CoRR, 2024)

Quantile deep learning models for multi-step ahead time series prediction. - Jimmy Cheung; Smruthi Rangarajan; Amelia Maddocks; Xizhe Chen; Rohitash Chandra (CoRR, 2024)

Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels. - Eric Chen; Martin S. Andersen 003; Rohitash Chandra (Environ. Model. Softw., 2024)

A clustering and graph deep learning-based framework for COVID-19 drug repurposing. - Chaarvi Bansal; P. R. Deepa; Vinti Agarwal; Rohitash Chandra (Expert Syst. Appl., 2024)

A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation. - Azal Ahmad Khan; Omkar Chaudhari; Rohitash Chandra (Expert Syst. Appl., 2024)

Sequential reversible jump MCMC for dynamic Bayesian neural networks. - Nhat Minh Nguyen; Minh-Ngoc Tran; Rohitash Chandra (Neurocomputing, 2024)

An Evaluation of LLMs and Google Translate for Translation of Selected Indian Languages via Sentiment and Semantic Analyses. - Rohitash Chandra; Aryan Chaudhari; Yeshwanth Rayavarapu (IEEE Access, 2025)

Large language models for newspaper sentiment analysis during COVID-19: The Guardian. - Rohitash Chandra; Baicheng Zhu; Qingying Fang; Eka Shinjikashvili (Appl. Soft Comput., 2025)

Multi-modal deep learning for credit rating prediction using text and numerical data streams. - Mahsa Tavakoli; Rohitash Chandra; Fengrui Tian; Cristián Bravo (Appl. Soft Comput., 2025)

Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems. - Saman Forouzandeh; Pavel N. Krivitsky; Rohitash Chandra (Expert Syst. Appl., 2025)

Pedestrian trajectory prediction using goal-driven and dynamics-based deep learning framework. - Honghui Wang; Weiming Zhi; Gustavo Batista; Rohitash Chandra (Expert Syst. Appl., 2025)

HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs. - Ashutosh Singh; Rohitash Chandra (CoRR, 2025)

Compact Bayesian Neural Networks via pruned MCMC sampling. - Ratneel Deo; Scott A. Sisson; Jody M. Webster; Rohitash Chandra (CoRR, 2025)

A Machine Learning Framework for Handling Unreliable Absence Label and Class Imbalance for Marine Stinger Beaching Prediction. - Amuche Ibenegbu; Amandine Schaeffer; Pierre Lafaye de Micheaux; Rohitash Chandra (CoRR, 2025)

Longitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues using LLMs. - Rohitash Chandra; Guoxiang Ren; Group-H (CoRR, 2025)

Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies. - Tanay Panat; Rohitash Chandra (CoRR, 2025)

Convolutional neural networks for mineral prospecting through alteration mapping with remote sensing data. - Ehsan Farahbakhsh; Dakshi Goel; Dhiraj Pimparkar; R. Dietmar Müller; Rohitash Chandra (CoRR, 2025)

Research impact evaluation based on effective authorship contribution sensitivity: h-leadership index. - Hardik A. Jain; Rohitash Chandra (CoRR, 2025)

Evaluation of LLMs for mathematical problem solving. - Ruonan Wang; Runxi Wang; Yunwen Shen; Chengfeng Wu; Qinglin Zhou; Rohitash Chandra (CoRR, 2025)

An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3. - Brendan Sands; Yining Wang; Chenhao Xu; Yuxuan Zhou; Lai Wei; Rohitash Chandra (CoRR, 2025)

Spatiotemporal deep learning models for detection of rapid intensification in cyclones. - Vamshika Sutar; Amandeep Singh; Rohitash Chandra (CoRR, 2025)

Abusive text transformation using LLMs. - Rohitash Chandra; Jiyong Choi (CoRR, 2025)

Deep learning framework for crater detection and identification on the Moon and Mars. - Yihan Ma 008; Zeyang Yu; Rohitash Chandra (CoRR, 2025)