Cover Image

The Evolution of Learning Algorithms for Artificial Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Baxter, Jonathan
Format:	Preprint
Published:	2025
Subjects:	Neural and Evolutionary Computing Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differential Evolution Algorithm based Hyper-Parameters Selection of Transformer Neural Network Model for Load Forecasting
by: Sen, Anuvab, et al.
Published: (2023)

CHNNet: An Artificial Neural Network With Connected Hidden Neurons
by: Shahir, Rafiad Sadat, et al.
Published: (2023)

Bio-Inspired Adaptive Neurons for Dynamic Weighting in Artificial Neural Networks
by: Islam, Ashhadul, et al.
Published: (2024)

A Neural-Evolutionary Algorithm for Autonomous Transit Network Design
by: Holliday, Andrew, et al.
Published: (2024)

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization
by: Gu, Shengda, et al.
Published: (2025)

Learning Long Sequences in Spiking Neural Networks
by: Stan, Matei Ioan, et al.
Published: (2023)

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
by: Pierro, Alessandro, et al.
Published: (2025)

Neural Algorithmic Reasoning for Combinatorial Optimisation
by: Georgiev, Dobrik, et al.
Published: (2023)

Multiple Population Alternate Evolution Neural Architecture Search
by: Zou, Juan, et al.
Published: (2024)

Effects of Introducing Synaptic Scaling on Spiking Neural Network Learning
by: Touda, Shinnosuke, et al.
Published: (2026)

Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning
by: Chen, Jiechen, et al.
Published: (2025)

Structure of Artificial Neural Networks -- Empirical Investigations
by: Stier, Julian
Published: (2024)

Airborne Neural Network
by: Ranjan, Paritosh, et al.
Published: (2025)

Cyclic Neural Network
by: Yang, Liangwei, et al.
Published: (2024)

S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks
by: Apolinario, Marco Paul E., et al.
Published: (2023)

Spiking Neural Networks with Random Network Architecture
by: Dai, Zihan, et al.
Published: (2025)

Understanding Vector-Valued Neural Networks and Their Relationship with Real and Hypercomplex-Valued Neural Networks
by: Valle, Marcos Eduardo
Published: (2023)

Looped Transformers are Better at Learning Learning Algorithms
by: Yang, Liu, et al.
Published: (2023)

Input Invex Neural Network
by: Sapkota, Suman, et al.
Published: (2021)

Physics-Modeled Neural Networks
by: Felipe-Sosa, Raul, et al.
Published: (2026)

Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
by: Pes, Lorenzo, et al.
Published: (2025)

EchoSpike Predictive Plasticity: An Online Local Learning Rule for Spiking Neural Networks
by: Graf, Lars, et al.
Published: (2024)

Supervised Spike Agreement Dependent Plasticity for Fast Local Learning in Spiking Neural Networks
by: S, Gouri Lakshmi, et al.
Published: (2026)

Rethinking Deep Learning: Non-backpropagation and Non-optimization Machine Learning Approach Using Hebbian Neural Networks
by: Itoh, Kei
Published: (2024)

Pareto-Optimal Anytime Algorithms via Bayesian Racing
by: Wurth, Jonathan, et al.
Published: (2026)

Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks
by: Wang, Jiachuan, et al.
Published: (2023)

Self-Supervised Neural Architecture Search for Multimodal Deep Neural Networks
by: Suzuki, Shota, et al.
Published: (2025)

ChronoPlastic Spiking Neural Networks
by: Chaudhry, Sarim
Published: (2025)

Multi Part Deployment of Neural Network
by: Ranjan, Paritosh, et al.
Published: (2025)

Multi-Objective Evolutionary Neural Architecture Search for Recurrent Neural Networks
by: Booysen, Reinhard, et al.
Published: (2024)

Deep Pulse-Coupled Neural Networks
by: Yi, Zexiang, et al.
Published: (2023)

Extensional Properties of Recurrent Neural Networks
by: Dantsin, Evgeny, et al.
Published: (2024)

SNNAX -- Spiking Neural Networks in JAX
by: Lohoff, Jamie, et al.
Published: (2024)

Utilizing Evolution Strategies to Train Transformers in Reinforcement Learning
by: Lorenc, Matyáš, et al.
Published: (2025)

Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning
by: Gao, Chengqian, et al.
Published: (2024)

EvIL: Evolution Strategies for Generalisable Imitation Learning
by: Sapora, Silvia, et al.
Published: (2024)

Towards Scalable Lottery Ticket Networks using Genetic Algorithms
by: Schönberger, Julian, et al.
Published: (2025)

Automated Metaheuristic Algorithm Design with Autoregressive Learning
by: Zhao, Qi, et al.
Published: (2024)

Deep Learning-Based Operators for Evolutionary Algorithms
by: Shem-Tov, Eliad, et al.
Published: (2024)

Topology-Aware Activation Functions in Neural Networks
by: Snopov, Pavel, et al.
Published: (2025)