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Recovering Population Dynamics from a Single Point Cloud Snapshot
Discovering population dynamics from point cloud data has experienced increased popularity in various applications, including GPS behavior...
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Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data
Single-cell technologies enable high-resolution studies of phenotype-defining molecular mechanisms. However, data sparsity and cellular heterogeneity...
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Swarm Intelligence Research: From Bio-inspired Single-population Swarm Intelligence to Human-machine Hybrid Swarm Intelligence
Swarm intelligence has become a hot research field of artificial intelligence. Considering the importance of swarm intelligence for the future...
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Fine-Grained Cooperative Coevolution in a Single Population: Between Evolution and Swarm Intelligence
Particle Swarm Optimisation (PSO) and Evolutionary Algorithms (EAs) differ in various ways, in particular with respect to information sharing and...
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Predicting Brain Multigraph Population from a Single Graph Template for Boosting One-Shot Classification
A central challenge in training one-shot learning models is the limited representativeness of the available shots of the data space. Particularly in...
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Identifying Systematic Variation at the Single-Cell Level by Leveraging Low-Resolution Population-Level Data
A major limitation in single-cell genomics is a lack of ability to conduct cost-effective population-level studies. As a result, much of the current...
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Multiple sclerosis: an associated single-nucleotide polymorphism study on Egyptian population
Multiple Sclerosis (MS) is an autoimmune disease that severely impacts the central nervous system. Thanks to the evolutionary genetic information...
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Evolutionary Multi-Task Optimization Foundations and Methodologies
A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be...
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Creating FCM Models from Quantitative Data with Evolutionary Algorithms
The weights of an FCM can be adjusted or entirely learned from data, which addresses limitations when experts are either unsure or unavailable. In...
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Object Tracking Technology Trends, Challenges and Applications
With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with...
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Machine Learning Applications of Evolutionary and Metaheuristic Algorithms
Evolutionary algorithms and other meta-heuristic approaches enjoy widespread popularity when dealing with challenging engineering design problems...
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A Radically New Theory of How the Brain Represents and Computes with Probabilities
It is widely believed that the brain implements probabilistic reasoning and that it represents information via some form of population (distributed)...
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Application of the Hierarchic Memetic Strategy HMS in Neuroevolution
Quite recently some noteworthy papers appeared showing classes of deep neural network (DNN) training tasks where rather simple one-population...
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Analysis of Nonlinear Optimization Problems Using Differential Evolution Algorithm
Differential evolution algorithm (DE) is a stochastic, population-based optimization approach for resolving nonlinear optimization issues....
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A Simple Hybrid Local Search Algorithm for Solving Optimization Problems
Optimization in engineering is an important domain of operations research that gains a lot of attention nowadays. Optimization may be constrained or...
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MPF-FS: A multi-population framework based on multi-objective optimization algorithms for feature selection
Feature selection algorithms based on evolutionary computation have continued to emerge, and most of them have achieved outstanding results. However,...
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Teacher-apprentices RL (TARL): leveraging complex policy distribution through generative adversarial hypernetwork in reinforcement learning
Typically, a Reinforcement Learning (RL) algorithm focuses in learning a single deployable policy as the end product. Depending on the initialization...
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scFBApy: A Python Framework for Super-Network Flux Balance Analysis
Constraint-based modelling (CBM) is a computational method used in systems biology to predict metabolic fluxes. However, modelling metabolic fluxes...
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Multi-atlas Representations Based on Graph Convolutional Networks for Autism Spectrum Disorder Diagnosis
Constructing functional connectivity (FC) based on brain atlas is a common approach to autism spectrum disorder (ASD) diagnosis, which is a...
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Test Case Generator for Problems of Complete Coverage and Path Planning for Emergency Response by UAVs
Unmanned Aerial Vehicles (UAVs) can aid rescue workers during operational emergency response procedures in tasks such as communication delivery or...