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09/16/2023
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning
Pedestrian trajectory prediction plays an important role in autonomous d...
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06/24/2023
A clustering and graph deep learning-based framework for COVID-19 drug repurposing
Drug repurposing (or repositioning) is the process of finding new therap...
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06/23/2023
An analysis of vaccine-related sentiments from development to deployment of COVID-19 vaccines
Anti-vaccine sentiments have been well-known and reported throughout the...
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04/06/2023
A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number o...
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04/02/2023
Bayesian neural networks via MCMC: a Python-based tutorial
Bayesian inference provides a methodology for parameter estimation and u...
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02/28/2023
Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron
Topic modelling with innovative deep learning methods has gained interes...
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02/28/2023
An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis
Google Translate has been prominent for language translation; however, l...
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01/26/2023
Reef-insight: A framework for reef habitat mapping with clustering methods via remote sensing
Environmental damage has been of much concern, particularly coastal area...
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01/25/2023
Recursive deep learning framework for forecasting the decadal world economic outlook
Gross domestic product (GDP) is the most widely used indicator in macroe...
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08/04/2022
Evolutionary bagging for ensemble learning
Ensemble learning has gained success in machine learning with major adva...
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08/01/2022
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19
Due to the rapid evolution of the SARS-CoV-2 (COVID-19) virus, a number ...
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05/23/2022
Artificial intelligence for topic modelling in Hindu philosophy: mapping themes between the Upanishads and the Bhagavad Gita
A distinct feature of Hindu religious and philosophical text is that the...
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04/24/2022
MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling Problem
The resource constrained project scheduling problem (RCPSP) is an NP-Har...
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01/18/2022
Surrogate-assisted distributed swarm optimisation for computationally expensive models
Advances in parallel and distributed computing have enabled efficient im...
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01/09/2022
Semantic and sentiment analysis of selected Bhagavad Gita translations using BERT-based language framework
It is well known that translations of songs and poems not only breaks rh...
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08/06/2021
SMOTified-GAN for class imbalanced pattern classification problems
Class imbalance in a dataset is a major problem for classifiers that res...
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04/17/2021
Bayesian graph convolutional neural networks via tempered MCMC
Deep learning models, such as convolutional neural networks, have long b...
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04/13/2021
Revisiting Bayesian Autoencoders with MCMC
Autoencoders gained popularity in the deep learning revolution given the...
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04/11/2021
Memory Capacity of Neural Turing Machines with Matrix Representation
It is well known that recurrent neural networks (RNNs) faced limitations...
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03/13/2021
A review of machine learning in processing remote sensing data for mineral exploration
As a primary step in mineral exploration, a variety of features are mapp...
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10/16/2019
Application of three-dimensional weights of evidence in modeling concealed ore deposits: Case study of a porphyry Cu deposit in the Urmia-Dokhtar magmatic belt of Iran
Given the challenges in data acquisition and modeling at the stage of de...
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12/12/2018
Surrogate-assisted Bayesian inversion for landscape and basin evolution models
The complex and computationally expensive features of the forward landsc...
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12/02/2018
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success
The rigorous quantification of uncertainty in geophysical inversions is ...
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11/21/2018
Surrogate-assisted parallel tempering for Bayesian neural learning
Parallel tempering addresses some of the drawbacks of canonical Markov C...
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11/11/2018
Langevin-gradient parallel tempering for Bayesian neural learning
Bayesian neural learning feature a rigorous approach to estimation and u...
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10/04/2018
Computer vision-based framework for extracting geological lineaments from optical remote sensing data
The extraction of geological lineaments from digital satellite data is a...
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08/06/2018
BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics
Estimating the impact of environmental processes on vertical reef develo...
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06/23/2018
Multi-core parallel tempering Bayeslands for basin and landscape evolution
In recent years, Bayesian inference has become a popular methodology for...
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05/02/2018
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands
Bayesian inference provides a principled approach towards uncertainty qu...
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08/22/2017
Stacked transfer learning for tropical cyclone intensity prediction
Tropical cyclone wind-intensity prediction is a challenging task conside...
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02/27/2017
Co-evolutionary multi-task learning for dynamic time series prediction
Multi-task learning employs shared representation of knowledge for learn...
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01/02/2017
An affective computational model for machine consciousness
In the past, several models of consciousness have become popular and hav...
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02/03/2015