Cover Image

A convolutional neural network deep learning method for model class selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Impraimakis, Marios
Format:	Preprint
Published:	2025
Subjects:	Systems and Control Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning Signal Processing 68T05 (Learning and adaptive systems) 93C95 (Neural networks in control theory) I.2.6; I.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep recurrent-convolutional neural network learning and physics Kalman filtering comparison in dynamic load identification
by: Impraimakis, Marios
Published: (2025)

A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning: Z24 Bridge structural health monitoring benchmark validation
by: Impraimakis, Marios, et al.
Published: (2025)

A Kullback-Leibler divergence method for input-system-state identification
by: Impraimakis, Marios
Published: (2025)

An unscented Kalman filter method for real time input-parameter-state estimation
by: Impraimakis, Marios, et al.
Published: (2025)

Graph Neural Networks for Efficient AC Power Flow Prediction in Power Grids
by: Talebi, Seyedamirhossein, et al.
Published: (2025)

FairEquityFL -- A Fair and Equitable Client Selection in Federated Learning for Heterogeneous IoV Networks
by: Islam, Fahmida, et al.
Published: (2025)

LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller
by: Djebko, Kirill, et al.
Published: (2025)

FDQN: A Flexible Deep Q-Network Framework for Game Automation
by: Gujavarthy, Prabhath Reddy
Published: (2024)

Learning coordinated badminton skills for legged manipulators
by: Ma, Yuntao, et al.
Published: (2025)

Transformer self-attention encoder-decoder with multimodal deep learning for response time series forecasting and digital twin support in wind structural health monitoring
by: Zhou, Feiyu, et al.
Published: (2026)

A Review of Machine Learning for Cavitation Intensity Recognition in Complex Industrial Systems
by: Sha, Yu, et al.
Published: (2025)

Evolving machine learning workflows through interactive AutoML
by: Barbudo, Rafael, et al.
Published: (2024)

An Information-Theoretic Method for Dynamic System Identification With Output-Only Damping Estimation
by: Impraimakis, Marios, et al.
Published: (2026)

Mimosa Framework: Toward Evolving Multi-Agent Systems for Scientific Research
by: Legrand, Martin, et al.
Published: (2026)

Improving LLM Agent Planning with In-Context Learning via Atomic Fact Augmentation and Lookahead Search
by: Holt, Samuel, et al.
Published: (2025)

Reward-Modulated Local Learning in Spiking Encoders: Controlled Benchmarks with STDP and Hybrid Rate Readouts
by: Chakraborty, Debjyoti
Published: (2026)

An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
by: Saini, Saurabh, et al.
Published: (2026)

CosmoCore-Evo: Evolutionary Dream-Replay Reinforcement Learning for Adaptive Code Generation
by: Ravindran, Santhosh Kumar
Published: (2025)

Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks
by: Nowotny, Thomas, et al.
Published: (2022)

ElasticFlow: One-Step Physics-Consistent Policy with Elastic Time Horizons for Language-Guided Manipulation
by: Chen, Kewei, et al.
Published: (2026)

Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image Classification
by: Hoang, Anh T., et al.
Published: (2023)

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
by: Johnson, David R., et al.
Published: (2025)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

CellARC: Measuring Intelligence with Cellular Automata
by: Lžičař, Miroslav
Published: (2025)

Autonomous AI Agents for Real-Time Affordable Housing Site Selection: Multi-Objective Reinforcement Learning Under Regulatory Constraints
by: Imanov, Olaf Yunus Laitinen, et al.
Published: (2026)

Resource-constrained Amazons chess decision framework integrating large language models and graph attention
by: Qian, Tianhao, et al.
Published: (2026)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Emotion-Inspired Learning Signals (EILS): A Homeostatic Framework for Adaptive Autonomous Agents
by: Tiwari, Dhruv
Published: (2025)

A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot
by: Jalaeian-Farimani, Mohsen, et al.
Published: (2026)

Combining Trained Models in Reinforcement Learning
by: Patil, Ujjwal, et al.
Published: (2026)

SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
by: Mishra, Satyam, et al.
Published: (2025)

KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
by: Brown, Jason R, et al.
Published: (2025)

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds
by: Sasso, Remo, et al.
Published: (2025)

Efficient Contextual Preferential Bayesian Optimization with Historical Examples
by: Khan, Farha A., et al.
Published: (2022)

Modeling and Controlling Deployment Reliability under Temporal Distribution Shift
by: Rahman, Naimur, et al.
Published: (2026)

Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches
by: Sasso, Remo, et al.
Published: (2025)

GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
by: Zhang, He, et al.
Published: (2026)

A Comparison Between Decision Transformers and Traditional Offline Reinforcement Learning Algorithms
by: Caunhye, Ali Murtaza, et al.
Published: (2025)

Learning from Preferences and Mixed Demonstrations in General Settings
by: Brown, Jason R, et al.
Published: (2025)

Rapid training of Hamiltonian graph networks using random features
by: Rahma, Atamert, et al.
Published: (2025)