主题图谱 / neural and evolutionary computing

neural and evolutionary computing

GeneTech 知识引擎共收录 352 篇相关科研实体，横跨 22 个垂直领域。数据来自 OpenAlex、arXiv、Crossref、PubMed、Europe PMC 等公开学术源，全部可溯源到原文。

年度产出趋势

相关主题

代表性文献（按质量分排序，前 60 条）

• DNA Reservoir Computing: A Novel Molecular Computing Approach
  2013 · 生物计算 · We propose a novel molecular computing approach based on reservoir computing. In reservoir computing, a dynamical core, called a reservoir, is perturbed with an external input signal while a readout layer maps the reserv…
• Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI
  2026 · AI 安全与对齐 · Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, including neural architecture search (NAS) guided by device-level metrics…
• Masked Autoencoders Learn Perception-Relevant Representations from Resting State Neural Data
  2026 · 仿生智能 · Clinical neuroprosthetics face a data bottleneck: labeled perception trials are scarce while hours of spontaneous neural activity are largely underutilized. Here, we test whether self-supervised learning can use these un…
• EvoFlow: Evolving Diverse Agentic Workflows On The Fly
  2025 · AI Agent 生态 · The past two years have witnessed the evolution of large language model (LLM)-based multi-agent systems from labor-intensive manual design to partial automation (\textit{e.g.}, prompt engineering, communication topology)…
• On the Depth of Monotone ReLU Neural Networks and ICNNs
  2025 · AI 安全与对齐 · We study two models of ReLU neural networks: monotone networks (ReLU$^+$) and input convex neural networks (ICNN). Our focus is on expressivity, mostly in terms of depth, and we prove the following lower bounds. For the …
• Learning to Measure Quantum Neural Networks
  2025 · 量子材料 · The rapid progress in quantum computing (QC) and machine learning (ML) has attracted growing attention, prompting extensive research into quantum machine learning (QML) algorithms to solve diverse and complex problems. D…
• Activation degree thresholds and expressiveness of polynomial neural networks
  2024 · AI 安全与对齐 · We study the expressive power of deep polynomial neural networks through the geometry of their neurovariety. We introduce the notion of the activation degree threshold of a network architecture to express when the dimens…
• Convergence Analysis for Deep Sparse Coding via Convolutional Neural Networks
  2024 · AI 安全与对齐 · In this work, we explore the intersection of sparse coding theory and deep learning to enhance our understanding of feature extraction capabilities in advanced neural network architectures. We begin by introducing a nove…
• Activations Through Extensions: A Framework To Boost Performance Of Neural Networks
  2024 · AI 安全与对齐 · Activation functions are non-linearities in neural networks that allow them to learn complex mapping between inputs and outputs. Typical choices for activation functions are ReLU, Tanh, Sigmoid etc., where the choice gen…
• Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack
  2024 · 具身智能 · Robotic technologies have been an indispensable part for improving human productivity since they have been helping humans in completing diverse, complex, and intensive tasks in a fast yet accurate and efficient way. Ther…
• Quantum Machine Learning Architecture Search via Deep Reinforcement Learning
  2024 · 量子计算 · The rapid advancement of quantum computing (QC) and machine learning (ML) has given rise to the burgeoning field of quantum machine learning (QML), aiming to capitalize on the strengths of quantum computing to propel ML …
• Quantum Machine Learning Architecture Search via Deep Reinforcement Learning
  2024 · 量子材料 · The rapid advancement of quantum computing (QC) and machine learning (ML) has given rise to the burgeoning field of quantum machine learning (QML), aiming to capitalize on the strengths of quantum computing to propel ML …
• Leveraging Residue Number System for Designing High-Precision Analog Deep Neural Network Accelerators
  2023 · 智慧农业 · Achieving high accuracy, while maintaining good energy efficiency, in analog DNN accelerators is challenging as high-precision data converters are expensive. In this paper, we overcome this challenge by using the residue…
• Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent
  2023 · AI 安全与对齐 · Prior attacks on graph neural networks have mostly focused on graph poisoning and evasion, neglecting the network's weights and biases. Traditional weight-based fault injection attacks, such as bit flip attacks used for …
• EEGSN: Towards Efficient Low-latency Decoding of EEG with Graph Spiking Neural Networks
  2023 · AI 安全与对齐 · A vast majority of spiking neural networks (SNNs) are trained based on inductive biases that are not necessarily a good fit for several critical tasks that require low-latency and power efficiency. Inferring brain behavi…
• Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
  2023 · 仿生智能 · Providing a model that achieves a strong predictive performance and is simultaneously interpretable by humans is one of the most difficult challenges in machine learning research due to the conflicting nature of these tw…
• Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
  2023 · 脑科学 · Providing a model that achieves a strong predictive performance and is simultaneously interpretable by humans is one of the most difficult challenges in machine learning research due to the conflicting nature of these tw…
• Alternating Bi-Objective Optimization for Explainable Neuro-Fuzzy Systems
  2026 · AI 安全与对齐 · Fuzzy systems show strong potential in explainable AI due to their rule-based architecture and linguistic variables. Existing approaches navigate the accuracy-explainability trade-off either through evolutionary multi-ob…
• Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization
  2026 · AI 安全与对齐 · Symbolic regression (SR) aims to discover mathematical expressions from data, a task traditionally tackled using Genetic Programming (GP) through combinatorial search over symbolic structures. Latent Space Optimization (…
• Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing
  2026 · 生物计算 · In this paper, we present a neuro-inspired approach to reservoir computing (RC) in which a network of in vitro cultured cortical neurons serves as the physical reservoir. Rather than relying on artificial recurrent model…
• Hybrid multi-objective evolutionary algorithms for service placement in the computing continuum: a comparative study with genetic traceability
  2026 · 生物计算 · This paper addresses multi-objective service placement in computing continuum environments through a collaborative hybrid island-model MOEA. The key innovation is not the design of a new general hybrid algorithm, but the…
• Computing with Living Neurons: Chaos-Controlled Reservoir Computing with Knowledge Transplant
  2026 · 生物计算 · We introduce chaos-controlled Reservoir Computing (cc-RC) for living neural cultures: dynamically rich substrates of unique potential for adaptive computation. To account for intrinsic biological variability, cc-RC combi…
• Improving Evaluation of Recombination-based Cartesian Genetic Programming
  2026 · 生物计算 · Cartesian Genetic Programming has traditionally been using mutation as its main and often sole genetic operator to drive evolutionary search. Despite advancements in recent years, recombinationbased approaches have long …
• Electronic Bursting Neuron: design, equations and hardware implementation
  2026 · 仿生智能 · Electronic neurons are a keystone for construction of the spiking neural networks which have numerous applications in neuroprosthetics, artificial memory, intensive calculations etc. A number of concepts of electronic ne…
• Event-based Neural Decoding for Neuroprosthetic Motor Control
  2026 · 仿生智能 · A substantial number of patients experience diminished mobility due to disabilities, diseases, or accidents. Although modern prostheses, powered by deep neural networks, hold the promise of significantly enhancing the qu…
• NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning
  2026 · 脑科学 · In a continual learning setting, we require a model to be plastic enough to learn a new task and stable enough to not disturb previously learned capabilities. We argue that this dilemma has an architectural root. A finit…
• Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part III -- Gradient Descent, Neural Plasticity, and the Emergence of Deep Intelligence
  2026 · 脑科学 · In Parts I and II of this series, we established isomorphisms between ant colony decision-making and two major families of ensemble learning: random forests (parallel, variance reduction) and boosting (sequential, bias r…
• A Comprehensive Review of Bio-Inspired Approaches to Coordination, Communication, and System Architecture in Underwater Swarm Robotics
  2026 · 深海科技 · The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising fra…
• Life as Plasmas: Autonomy and Interactivism in-materio
  2026 · 地外科学 · When is a material system a candidate for life at all? We argue that this question is prior to behavior, functional architecture, or computational capacity, and that at root it is one of physical admissibility. We develo…
• Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems
  2025 · AI 安全与对齐 · Neuromorphic Continual Learning (NCL) paradigm leverages Spiking Neural Networks (SNNs) to enable continual learning (CL) capabilities for AI systems to adapt to dynamically changing environments. Currently, the state-of…
• Gate-level boolean evolutionary geometric attention neural networks
  2025 · AI 安全与对齐 · This paper presents a gate-level Boolean evolutionary geometric attention neural network that models images as Boolean fields governed by logic gates. Each pixel is a Boolean variable (0 or 1) embedded on a two-dimension…
• Spiking Neural Network for Intra-cortical Brain Signal Decoding
  2025 · AI 安全与对齐 · Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep l…
• Towards spiking analog hardware implementation of a trajectory interpolation mechanism for smooth closed-loop control of a spiking robot arm
  2025 · AI 安全与对齐 · Neuromorphic engineering aims to incorporate the computational principles found in animal brains, into modern technological systems. Following this approach, in this work we propose a closed-loop neuromorphic control sys…
• Sufficient conditions for offline reactivation in recurrent neural networks
  2025 · AI 安全与对齐 · During periods of quiescence, such as sleep, neural activity in many brain circuits resembles that observed during periods of task engagement. However, the precise conditions under which task-optimized networks can auton…
• Game-Theoretic Gradient Control for Robust Neural Network Training
  2025 · AI 安全与对齐 · Feed-forward neural networks (FFNNs) are vulnerable to input noise, reducing prediction performance. Existing regularization methods like dropout often alter network architecture or overlook neuron interactions. This stu…
• Event-based Neural Spike Detection Using Spiking Neural Networks for Neuromorphic iBMI Systems
  2025 · AI 安全与对齐 · Implantable brain-machine interfaces (iBMIs) are evolving to record from thousands of neurons wirelessly but face challenges in data bandwidth, power consumption, and implant size. We propose a novel Spiking Neural Netwo…
• Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions
  2025 · AI 安全与对齐 · Gradient-based neural network training traditionally enforces symmetry between forward and backward propagation, requiring activation functions to be differentiable (or sub-differentiable) and strictly monotonic in certa…
• Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System
  2025 · 生物计算 · In this study, we explore how the combination of synthetic biology, neuroscience modeling, and neuromorphic electronic systems offers a new approach to creating an artificial system that mimics the natural sense of smell…
• HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing
  2025 · 生物计算 · In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 million neurons and 40 billion synapses - rou…
• From Neurons to Computation: Biological Reservoir Computing for Pattern Recognition
  2025 · 生物计算 · In this paper, we introduce a paradigm for reservoir computing (RC) that leverages a pool of cultured biological neurons as the reservoir substrate, creating a biological reservoir computing (BRC). This system operates s…
• A Computational Perspective on NeuroAI and Synthetic Biological Intelligence
  2025 · 生物计算 · NeuroAI is an emerging field at the intersection of neuroscience and artificial intelligence, where insights from brain function guide the design of intelligent systems. A central area within this field is synthetic biol…
• From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classification
  2025 · 生物计算 · In this paper, we present a biologically grounded approach to reservoir computing (RC), in which a network of cultured biological neurons serves as the reservoir substrate. This system, referred to as biological reservoi…
• TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming
  2025 · 生物计算 · Over the years, genetic programming (GP) has evolved, with many proposed variations, especially in how they represent a solution. Being essentially a program synthesis algorithm, it is capable of tackling multiple proble…
• Neural Associative Skill Memories for safer robotics and modelling human sensorimotor repertoires
  2025 · 仿生智能 · Modern robots face challenges shared by humans, where machines must learn multiple sensorimotor skills and express them adaptively. Equipping robots with a human-like memory of how it feels to do multiple stereotypical m…
• Predicting concentration levels of air pollutants by transfer learning and recurrent neural network
  2025 · 仿生智能 · Air pollution (AP) poses a great threat to human health, and people are paying more attention than ever to its prediction. Accurate prediction of AP helps people to plan for their outdoor activities and aids protecting h…
• Exoplanet formation inference using conditional invertible neural networks
  2025 · 仿生智能 · The interpretation of the origin of observed exoplanets is usually done only qualitatively due to uncertainties of key parameters in planet formation models. To allow a quantitative methodology which traces back in time …
• Predicting concentration levels of air pollutants by transfer learning and recurrent neural network
  2025 · 脑科学 · Air pollution (AP) poses a great threat to human health, and people are paying more attention than ever to its prediction. Accurate prediction of AP helps people to plan for their outdoor activities and aids protecting h…
• IP$^{2}$-RSNN: Bi-level Intrinsic Plasticity Enables Learning-to-learn in Recurrent Spiking Neural Networks
  2025 · 脑科学 · Learning-to-learn (L2L), defined as progressively faster learning across similar tasks, is fundamental to both neuroscience and artificial intelligence. However, its neural basis remains elusive, as most studies emphasiz…
• Reinitializing weights vs units for maintaining plasticity in neural networks
  2025 · 脑科学 · Loss of plasticity is a phenomenon in which a neural network loses its ability to learn when trained for an extended time on non-stationary data. It is a crucial problem to overcome when designing systems that learn cont…
• Exoplanet formation inference using conditional invertible neural networks
  2025 · 脑科学 · The interpretation of the origin of observed exoplanets is usually done only qualitatively due to uncertainties of key parameters in planet formation models. To allow a quantitative methodology which traces back in time …
• NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
  2025 · 脑科学 · Spiking Neural Networks (SNNs) are computational models inspired by the structure and dynamics of biological neuronal networks. Their event-driven nature enables them to achieve high energy efficiency, particularly when …
• A flexible framework for structural plasticity in GPU-accelerated sparse spiking neural networks
  2025 · 脑科学 · The majority of research in both training Artificial Neural Networks (ANNs) and modeling learning in biological brains focuses on synaptic plasticity, where learning equates to changing the strength of existing connectio…
• Learning with Spike Synchrony in Spiking Neural Networks
  2025 · 脑科学 · Spiking neural networks (SNNs) promise energy-efficient computation by mimicking biological neural dynamics, yet existing plasticity rules focus on isolated spike pairs and fail to leverage the synchronous activity patte…
• Neuromorphic Simulation of Drosophila Melanogaster Brain Connectome on Loihi 2
  2025 · 脑科学 · We demonstrate the first-ever nontrivial, biologically realistic connectome simulated on neuromorphic computing hardware. Specifically, we implement the whole-brain connectome of the adult Drosophila melanogaster (fruit …
• A Computational Perspective on NeuroAI and Synthetic Biological Intelligence
  2025 · 具身智能 · NeuroAI is an emerging field at the intersection of neuroscience and artificial intelligence, where insights from brain function guide the design of intelligent systems. A central area within this field is synthetic biol…
• Predicting concentration levels of air pollutants by transfer learning and recurrent neural network
  2025 · 具身智能 · Air pollution (AP) poses a great threat to human health, and people are paying more attention than ever to its prediction. Accurate prediction of AP helps people to plan for their outdoor activities and aids protecting h…
• Guiding Evolution of Artificial Life Using Vision-Language Models
  2025 · 地外科学 · Foundation models (FMs) have recently opened up new frontiers in the field of artificial life (ALife) by providing powerful tools to automate search through ALife simulations. Previous work aligns ALife simulations with …
• Optimisation of Aircraft Maintenance Schedules
  2025 · 低空经济 · We present an aircraft maintenance scheduling problem, which requires suitably qualified staff to be assigned to maintenance tasks on each aircraft. The tasks on each aircraft must be completed within a given turn around…
• The Iterative Chainlet Partitioning Algorithm for the Traveling Salesman Problem with Drone and Neural Acceleration
  2025 · 低空经济 · This study introduces the Iterative Chainlet Partitioning (ICP) algorithm and its neural acceleration for solving the Traveling Salesman Problem with Drone (TSP-D). The proposed ICP algorithm decomposes a TSP-D solution …
• Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System
  2025 · 量子计算 · In this study, we explore how the combination of synthetic biology, neuroscience modeling, and neuromorphic electronic systems offers a new approach to creating an artificial system that mimics the natural sense of smell…

以 API 获取该主题全量数据

# 主题词表（含本主题的站点分布与年度分布）
curl http://data.swarmlabs.tools/api/topics.json

# 主题共现知识图谱
curl http://data.swarmlabs.tools/api/graph.json

需要按主题批量拉取、导出 BibTeX 或接入 AI Agent？查看 数据下载与格式 或 MCP 接入。