AUTOMATED WEATHER CLASSIFICATION USING TRANSFER LEARNING

Συγγραφείς: Vellore Institute of Technology University

Θεματικοί όροι: Deep Learning/statistics & numerical data, Machine Learning/classification, Deep Learning/history, Supervised Machine Learning, Deep Learning/standards, Deep Learning/classification, Machine Learning/standards, Deep Learning/trends

Residual Jacobian Physics-Informed Neural Networks (Rj-Pinns) for Guaranteed Convergence

Συγγραφείς: Dadesso, Dadoyi

Θεματικοί όροι: Data-Driven Modeling, Deep Learning/statistics & numerical data, Partial Differential Equations (PDEs), Physics, Computational science, Computer Simulation/statistics & numerical data, Machine Learning, Deep Learning, Engineering, Jacobian-based optimization, Artificial Intelligence, Trust-region methods for ML, Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs), Computer Science, FOS: Mathematics, Physics-Informed Neural Networks (PINNs), Mathematics

Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs) for improved convergence and stability

Συγγραφείς: Dadesso, Dadoyi

Θεματικοί όροι: Data-Driven Modeling, Deep Learning/statistics & numerical data, Partial Differential Equations (PDEs), Physics, Computational science, Computer Simulation/statistics & numerical data, Machine Learning, Deep Learning, Engineering, Jacobian-based optimization, Artificial Intelligence, Trust-region methods for ML, Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs), Computer Science, FOS: Mathematics, Physics-Informed Neural Networks (PINNs), Mathematics

IndiMorph: An AI-Powered Modular Morphing Mobility System for Multi-Terrain Adaptation

Συγγραφείς: SINGH, OM, Shukla, Jahnvi, orcid:0009-0009-4986-, Pandey, Gaurav, Srivastava, Manya, Dwivedi, Anushka, Srivastava, Yash

Θεματικοί όροι: Deep Learning/statistics & numerical data

Relation: https://zenodo.org/records/16741610; oai:zenodo.org:16741610; https://doi.org/10.36227/techrxiv.175432935.51798519/v1

Διαθεσιμότητα: https://doi.org/10.36227/techrxiv.175432935.51798519/v1
https://zenodo.org/records/16741610

Forecasting Labor Demand: Predicting JOLT Job Openings using Deep Learning Model

Συγγραφείς: Kim, Kyungsun, orcid:0009-0003-0869-

Θεματικοί όροι: Models, Economic, Neural Networks, Computer, Deep Learning/statistics & numerical data

Relation: https://zenodo.org/records/15091416; oai:zenodo.org:15091416; https://doi.org/10.5281/zenodo.15091416

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.15091416
https://zenodo.org/records/15091416

Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs) for improved convergence and stability ; Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs): A Robust Framework for Inverse Problems in PDEs ; Guaranteed-Convergence PINNs for Parameter Estimation ; Réseaux Neuronaux à Physique Intégrée par Jacobien Résiduel (RJ-PINNs) pour une Convergence Garantie

Συγγραφείς: Dadesso, Dadoyi

Συνεισφορές: Dadesso, Dadoyi

Θεματικοί όροι: Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs), Trust-region methods for ML, Physics-Informed Neural Networks (PINNs), Machine Learning, Partial Differential Equations (PDEs), Data-Driven Modeling, Jacobian-based optimization, Deep Learning, Deep Learning/statistics & numerical data, Computer Simulation/statistics & numerical data, Mathematics, Physics, Engineering, Computer Science, Artificial Intelligence, Computational science

Relation: https://zenodo.org/records/16956061; oai:zenodo.org:16956061; https://doi.org/10.5281/zenodo.16956061

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.16956061
https://zenodo.org/records/16956061

Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs) for Guaranteed Convergence ; Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs): A Robust Framework for Inverse Problems in PDEs ; Guaranteed-Convergence PINNs for Parameter Estimation ; Réseaux Neuronaux à Physique Intégrée par Jacobien Résiduel (RJ-PINNs) pour une Convergence Garantie

Συγγραφείς: Dadesso, Dadoyi

Συνεισφορές: Dadesso, Dadoyi

Θεματικοί όροι: Residual Jacobian Physics-Informed Neural Networks (RJ-PINNs), Trust-region methods for ML, Physics-Informed Neural Networks (PINNs), Machine Learning, Partial Differential Equations (PDEs), Data-Driven Modeling, Jacobian-based optimization, Deep Learning, Deep Learning/statistics & numerical data, Computer Simulation/statistics & numerical data, Mathematics, Physics, Engineering, Computer Science, Artificial Intelligence, Computational science

Relation: https://zenodo.org/records/16929905; oai:zenodo.org:16929905; https://doi.org/10.5281/zenodo.16929905

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.16929905
https://zenodo.org/records/16929905

Optimizing Retrieval in Libraries through RAG: A Framework

Συγγραφείς: Mukhopadhyay, Parthasarathi

Θεματικοί όροι: Deep Learning/statistics & numerical data, Large Language Model, Llama, Information Storage and Retrieval/methods, Conversational search, Retrieval Augmented Generation, LangChain

NEMoE__Neuro_Evolutionary_Mixture_of_Experts_Transformer

Συγγραφείς: Narayasamay, Ranjeeth

Θεματικοί όροι: Deep Learning/statistics & numerical data, Transformers, Neural Networks, Computer, Evolutionary Algorithms, Adaptive Architectures, Mixture of Experts, Language Modeling

Life Trajectories as Symbolic Language ; Exploring Human Behaviour with Language Models

Συγγραφείς: Savcisens, Germans, orcid:0000-0002-5811-

Συνεισφορές: Savcisens, Germans

Θεματικοί όροι: Natural Language Processing, Neural Networks, Computer, Deep Learning/ethics, Deep learning, Deep Learning/statistics & numerical data, Machine Learning, Mortality, Demography/statistics & numerical data, Demography, Data science, Computer and information sciences, Mathematics, Mathematics/methods, Artificial intelligence, Artificial Intelligence/statistics & numerical data, Data analysis

Relation: arXiv:2306.03009; https://zenodo.org/records/14706679; oai:zenodo.org:14706679; https://doi.org/10.5281/zenodo.14706679

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.14706679
https://zenodo.org/records/14706679
https://orbit.dtu.dk/en/publications/life-trajectories-as-symbolic-language

Governing Advanced Artificial Intelligence: The SMD, I-HVAGI⁺, and PD-TU Frameworks for Asymptotic Safety, Verifiable Self-Modification, and Computational Due Process

Συγγραφείς: Ivliev, Ihor, GenAI, LLMs

Θεματικοί όροι: Social security, Patient Medication Knowledge/methods, Computer Security/economics, Data Display/statistics & numerical data, I-HVAGI, Unsupervised Machine Learning/classification, Risk communication, Deep Learning/supply & distribution, Data Warehousing/statistics & numerical data, Security Measures/classification, Data Mining, Deep Learning/economics, Information Technology/ethics, Artificial Intelligence/ethics, Social Security/ethics, Information Technology/supply & distribution, Deep Learning/standards, Machine Learning/trends, Machine Learning/history, Knowledge, Risk Adjustment, Supervised Machine Learning, Knowledge Discovery/legislation & jurisprudence, I-HVAGI⁺, Artificial Intelligence/economics, Unsupervised Machine Learning/history, Data analysis, Epistemology, Trust, Risk Assessment, Deep Learning/legislation & jurisprudence, Deep Learning, Machine learning, Machine Learning/classification, Deep Learning/history, Artificial Intelligence/trends, Clinical Governance, Deep Learning/classification, Data mining, Knowledge engineering, Risk Management, Knowledge Management/standards, Data exchange, Deep learning, Knowledge Discovery/history, Risk management, E-governance, Data Curation/statistics & numerical data, Economic data, Deep Learning/trends, Big Data, Machine Learning/ethics, Artificial intelligence, Risk perception, Data base, Risk analysis, Knowledge Bases, Artificial Intelligence/standards, Residual risk, Machine Learning, Computer security, Risk Factors, Data networks, Machine Learning/standards, Risk assessment, Governance, SMD, Knowledge Management/economics, Network security, Knowledge organization, Knowledge Discovery, Data Collection/statistics & numerical data, Major risk, Data processing, Knowledge Management, Knowledge Discovery/methods, Artificial Intelligence/classification, Data Display, Information Technology/history, Risk, Deep Learning/statistics & numerical data, Security Measures, Artificial Intelligence/history, Risk-Taking, Indigenous knowledge, Artificial Intelligence, Supervised Machine Learning/standards, Computer Security, Ethics, AI Governance, Data Compression/statistics & numerical data, PD-TU, Information engineering, Data Science, Security Measures/standards, Statistical data, Machine Learning/economics, Deep Learning/ethics, Disaster risk, Risk reduction, Computer Security/classification, Data Management/statistics & numerical data, Data Science/statistics & numerical data, Unsupervised Machine Learning

Governing Advanced AI: Conceptual Frameworks for Self-Modification Defence, Alignment, and Transparent Oversight

Συγγραφείς: Ivliev, Ihor, GenAI, LLMs

Θεματικοί όροι: Social security, Patient Medication Knowledge/methods, Computer Security/economics, Data Display/statistics & numerical data, I-HVAGI, Unsupervised Machine Learning/classification, Risk communication, Deep Learning/supply & distribution, Data Warehousing/statistics & numerical data, Security Measures/classification, Data Mining, Deep Learning/economics, Information Technology/ethics, Artificial Intelligence/ethics, Social Security/ethics, Information Technology/supply & distribution, Deep Learning/standards, Machine Learning/trends, Machine Learning/history, Knowledge, Risk Adjustment, Supervised Machine Learning, Knowledge Discovery/legislation & jurisprudence, I-HVAGI⁺, Artificial Intelligence/economics, Unsupervised Machine Learning/history, Data analysis, Epistemology, Trust, Risk Assessment, Deep Learning/legislation & jurisprudence, Deep Learning, Machine learning, Machine Learning/classification, Deep Learning/history, Artificial Intelligence/trends, Clinical Governance, Deep Learning/classification, Data mining, Knowledge engineering, Risk Management, Knowledge Management/standards, Data exchange, Deep learning, Knowledge Discovery/history, Risk management, E-governance, Data Curation/statistics & numerical data, Economic data, Deep Learning/trends, Big Data, Machine Learning/ethics, Artificial intelligence, Risk perception, Data base, Risk analysis, Knowledge Bases, Artificial Intelligence/standards, Residual risk, Machine Learning, Computer security, Risk Factors, Data networks, Machine Learning/standards, Risk assessment, Governance, SMD, Knowledge Management/economics, Network security, Knowledge organization, Knowledge Discovery, Data Collection/statistics & numerical data, Major risk, Data processing, Knowledge Management, Knowledge Discovery/methods, Artificial Intelligence/classification, Data Display, Information Technology/history, Risk, Deep Learning/statistics & numerical data, Security Measures, Artificial Intelligence/history, Risk-Taking, Indigenous knowledge, Artificial Intelligence, Supervised Machine Learning/standards, Computer Security, Ethics, AI Governance, Data Compression/statistics & numerical data, PD-TU, Information engineering, Data Science, Security Measures/standards, Statistical data, Machine Learning/economics, Deep Learning/ethics, Disaster risk, Risk reduction, Computer Security/classification, Data Management/statistics & numerical data, Data Science/statistics & numerical data, Unsupervised Machine Learning

ARIEL: Advanced Reinforcement Incentives & Emotions based Learning

Συγγραφείς: Jason Langhorne, Mesiah Bishop

Θεματικοί όροι: Machine Learning/ethics, Artificial intelligence, Robotics/instrumentation, Artificial Intelligence/legislation & jurisprudence, Artificial Intelligence/statistics & numerical data, Swarm robotics, Quantum Dots/classification, Data Science/economics, Artificial Intelligence/standards, Robotics/economics, Probiotics/history, Unsupervised Machine Learning/classification, Data science, Machine Learning, Robotics/trends, Deep Learning/supply & distribution, Supervised Machine Learning/economics, Data Science/methods, Robotics/organization & administration, Deep Learning/economics, Machine Learning/standards, Robotics/methods, Artificial Intelligence/ethics, Supervised Machine Learning/ethics, Machine Learning/supply & distribution, Robotics/legislation & jurisprudence, Materials Science/statistics & numerical data, Robotics, Deep Learning/standards, Cognitive Science/statistics & numerical data, Robotics/history, Supervised Machine Learning/classification, Machine Learning/trends, Unsupervised Machine Learning/ethics, Robotics/classification, Machine Learning/history, Artificial Intelligence/classification, Data Science/classification, Supervised Machine Learning, Robotics/standards, Data Science/instrumentation, Deep Learning/statistics & numerical data, Artificial Intelligence/economics, Supervised Machine Learning/trends, Unsupervised Machine Learning/history, Data Science/trends, Soft robotics, Data Science/legislation & jurisprudence, Deep Learning/legislation & jurisprudence, Data Science/organization & administration, Artificial Intelligence/history, Military Science/statistics & numerical data, Deep Learning, Artificial Intelligence, Supervised Machine Learning/standards, Robotics/ethics, Machine learning, Machine Learning/classification, Environmental Science/statistics & numerical data, Deep Learning/history, Robotics/education, Quantum Theory/history, Artificial Intelligence/trends, Science/statistics & numerical data, Deep Learning/classification, Machine Learning/legislation & jurisprudence, Data Science/education, Robotics/statistics & numerical data, Probiotics, Data Science, Data Science/history, Quantum computers, Robotic surgery, Deep learning, Artificial Intelligence/supply & distribution, Machine Learning/economics, Deep Learning/ethics, Information Science/statistics & numerical data, Data Science/ethics, Data Science/standards, Quantum Theory, Data Science/statistics & numerical data, Neural Networks, Computer, Unsupervised Machine Learning, Deep Learning/trends

Detecting Cybersecurity Threats using Deep Learning

Συγγραφείς: Ali, Ratul

Θεματικοί όροι: Detecting Cybersecurity Threats using Deep Learning, cybersecurity, Deep learning, Deep Learning/statistics & numerical data

Relation: https://zenodo.org/records/17018250; oai:zenodo.org:17018250; https://doi.org/10.5281/zenodo.17018250

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.17018250
https://zenodo.org/records/17018250

Datasets for 'Energy Underprediction from Symmetry in Machine-Learning Interatomic Potentials'

Συγγραφείς: Nong, Wei, Zhu, Ruiming, orcid:0000-0002-6838-, Ren, Zekun, Hoffmann Petersen, Martin, Yamazaki, Shuya, Kazeev, Nikita, Ustyuzhanin, Andrey, Wu, Gang, Yang, Shuo-Wang, Hippalgaonkar, Kedar

Θεματικοί όροι: Computational Chemistry, Materials Science/statistics & numerical data, Deep Learning/statistics & numerical data, Machine Learning

Relation: https://zenodo.org/records/16074113; oai:zenodo.org:16074113; https://doi.org/10.5281/zenodo.16074113

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.16074113
https://zenodo.org/records/16074113

NeuriPhy - Neuroimaging Dataset for Physics-Informed Learning

Συγγραφείς: Assis, Tiago

Θεματικοί όροι: brain shift, Image registration, Deep Learning, Deep Learning/statistics & numerical data, Brain/surgery, Neurosurgery, Neuroimaging, Neuroimaging/methods, Machine learning, Supervised Machine Learning

Relation: https://zenodo.org/records/15381866; oai:zenodo.org:15381866; https://doi.org/10.5281/zenodo.15381866

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.15381866
https://zenodo.org/records/15381866

High-latitude Pacific Ocean Sediment Geochemistry and XRF Data for Geoscientific Foundation Models

Συγγραφείς: Lee, An-Sheng, orcid:0000-0002-5492-, Pao, Yu-Wen

Συνεισφορές: Lin, Hsuan-Tien, Liou, Sofia Ya Hsuan, Chao, Weng-si, Tiedemann, Ralf, Lembke-Jene, Lester, Lamy, Frank

Θεματικοί όροι: X-ray Fluorescence, Ocean chemistry, Marine sediment, Geochemistry, Calcium Carbonate, Total organic carbon, Core Scanning, Deep Learning/statistics & numerical data, South pacific ocean, North pacific ocean

Relation: https://zenodo.org/records/16354051; oai:zenodo.org:16354051; https://doi.org/10.5281/zenodo.16354051

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.16354051
https://zenodo.org/records/16354051

Gibbs randomness-compression proposition: An efficient deep learning

Συγγραφείς: Süzen, Mehmet, orcid:0000-0002-9460-

Θεματικοί όροι: Deep Learning/statistics & numerical data, Information Theory, Compressed sensing

Relation: https://zenodo.org/records/15751974; oai:zenodo.org:15751974; https://doi.org/10.5281/zenodo.15751974

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.15751974
https://zenodo.org/records/15751974

AudioSet-EV: an AudioSet-derived distribution of Emergency Vehicle Siren sounds

Συγγραφείς: Giacomelli, Stefano, orcid:0009-0009-0438-, Rinaldi, Claudia

Συνεισφορές: Giordano, Marco

Θεματικοί όροι: Sound, Sound Recordings, Deep Learning, Deep Learning/statistics & numerical data, AudioSet, Python, PyTorch, Datasets as Topic/statistics & numerical data

Relation: https://github.com/StefanoGiacomelli/audioset-tools/tree/main; https://zenodo.org/records/14882314; oai:zenodo.org:14882314; https://doi.org/10.5281/zenodo.14882314

Διαθεσιμότητα: https://doi.org/10.5281/zenodo.14882314
https://zenodo.org/records/14882314