AI & Machine Learning · Computer Science & AI
Neural & Evolutionary Computing
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324 papers, from 4 September 2026 to 5 November 2026: 324 arXiv preprints.
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Newest papers, page 11
Deep Learning Methods in Neuroscience: From Modeling Molecular Mechanisms to Classifying States of Consciousness
A critical analysis of contemporary approaches to the study of conscious states.EvE: An Alternate Optimizer to Adam
Adam and its variants dominate neural network training, but a single run only reveals whether a configuration works well after most of its budget is spent, a poor fit for hyperparameter or…Arbitrary-Accuracy Neural Approximation with Optimal Neuron Count and Near-Optimal Bit Complexity
We study the minimum number of hidden neurons required for arbitrary-accuracy approximation of multivariate Hölder-continuous functions on $[0,1]^d$ and the associated encoding complexity.CMDO: A Cognitive Memory-Driven Optimization Algorithm for Adaptive Population-Based Search
Population-based optimization methods often use previous search information through successful solutions, parameter adaptation, or operator performance, but they rarely retain the context in which a…Graph neural networks for sampling-invariant embeddings of organized signal sets
Sensor networks and radars can deliver signals as organized sets, e.g. ordered signals, signals describing range cells within a grid or signals perceived as graph nodes.HeurEvo: Agentic Evolution of Hybrid Solver-Augmented Heuristics for Time-Critical Mathematical Optimization
Recent advances in agentic heuristic design use AI agents and execution feedback to automate algorithm discovery for challenging optimization problems.Massively Parallel Reinforcement Learning with a Chaotic Reconfigurable Clockless Chip
Hardware accelerators based on physical dynamical systems offer an attractive route toward energy-efficient reinforcement learning applications.MorphAtt: A Neuromorphic Accelerator for Efficient Multi-Head Attention Processing in Spiking Vision Transformers
Spiking Vision Transformers (SViTs) are developed as an energy-efficient alternative to conventional ViTs for computer vision tasks at the edge.MTLiquid: Enabling Efficient Multi-Task Learning using Liquid Neural Networks for Lightweight Healthcare Monitoring Systems
Continuous-time sensing and monitoring with timely and accurate decision-making are critical for many real-world applications.APEX: An Extensible Model for Agent-Assisted Production Scheduling
Production scheduling requires realistic models that reflect operational constraints and efficient methods that balance competing goals.Raven: The Harness of Harnesses for Composable Agentic Intelligence
As large language models advance, AI agents are moving beyond isolated, domain-specific tasks toward long-horizon, cross-domain workflows.Program-Verified Self-Evolution for Vision-Language Models
Self-evolving vision-language models train on questions they generate from unlabeled images.Neuron-Level Architecture Growth: A Controlled Evaluation for EEG Time-Series Decoding
Convolutional EEG decoders are trained at a fixed width, usually set by their authors on other data.ADPTNet: Adaptive with Prescriptive Timescales Non-Linear SSM for Sequence Modelling
A central aim of neuromorphic computing is to provide a viable alternative to highly energy-intensive Transformer-based AI.DS-VLA: A Dendritic-inspired Vision-Language-Action Model for Robust Action Control
Vision-language-action (VLA) models have achieved strong performance in language-conditioned manipulation, yet success under nominal evaluation does not necessarily translate into robust closed-loop…All On-Board: Fully On-Chip Neuromorphic Q-Learning with Embedded CartPole Simulation
As AI models grow in size and usage, their energy demands increase dramatically, raising sustainability and economic concerns.Analog-Friendly Predictive Coding without Activation Derivatives
Predictive coding (PC) is a local, energy-based alternative to backpropagation (BP) whose iterative inference dynamics make it attractive for implementation on analog hardware.RIPE-MambaSpike: Resolution-Independent Spiking-State-Space Interfaces for Parameter-Efficient Event-Based Vision
Spiking-Mamba hybrids reach strong accuracy on event-based vision, but existing designs often require tens of millions of parameters.Structured Bayesian Modeling of Dynamic Receptive1 Fields in Salamander Retinal Ganglion Cells
Neurons in the visual system are selective for specific spatial and temporal stimulus features, described by their \emph{receptive field}.Landscape Limits of Quantum-Inspired Evolutionary Optimization across 256 continuous functions
Quantum-inspired evolutionary optimization (QIEO) represents design variables as a set of qubits and searches a continuous, multi-dimensional landscape through rotation of the qubit's amplitude pair.