Copertina

Statistical tuning of artificial neural network

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mohamad, Mohamad Yamen AL, Bevrani, Hossein, Haydari, Ali Akbar
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Applications
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Comparative analysis of two new wind speed T-X models using Weibull and log-logistic distributions for wind energy potential estimation in Tabriz, Iran
di: Mohammadpour, Meysam, et al.
Pubblicazione: (2024)

Bayesian neural networks for predicting uncertainty in full-field material response
di: Pasparakis, George D., et al.
Pubblicazione: (2024)

Can artificial intelligence predict clinical trial outcomes?
di: Jin, Shuyi, et al.
Pubblicazione: (2024)

Pruning neural network models for gene regulatory dynamics using data and domain knowledge
di: Hossain, Intekhab, et al.
Pubblicazione: (2024)

Statistical post-processing of visibility ensemble forecasts
di: Baran, Sándor, et al.
Pubblicazione: (2023)

Targeted tuning of random forests for quantile estimation and prediction intervals
di: Berkowitz, Matthew, et al.
Pubblicazione: (2025)

Analyses and Concerns in Precision Medicine: A Statistical Perspective
di: Chen, Xiaofei
Pubblicazione: (2024)

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
di: S, Saranya Ganesh, et al.
Pubblicazione: (2025)

Efficient modeling of sub-kilometer surface wind with Gaussian processes and neural networks
di: Zanetta, Francesco, et al.
Pubblicazione: (2024)

High-Dimensional Statistical Process Control via Manifold Fitting and Learning
di: Tas, Burak I., et al.
Pubblicazione: (2025)

Statistical Embeddings for Similarity, Retrieval, and Interpretable Alignment of Numeric Tabular Datasets
di: Kunz, M. Ross, et al.
Pubblicazione: (2026)

Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks
di: Longjohn, Rachel, et al.
Pubblicazione: (2025)

Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
di: Jiang, Jialong, et al.
Pubblicazione: (2025)

Modeling and Prediction of the UEFA EURO 2024 via Combined Statistical Learning Approaches
di: Groll, Andreas, et al.
Pubblicazione: (2024)

Statistical Reinforcement Learning in the Real World: A Survey of Challenges and Future Directions
di: Gazi, Asim H., et al.
Pubblicazione: (2026)

Ensemble Machine Learning and Statistical Procedures for Dynamic Predictions of Time-to-Event Outcomes
di: van Gerwen, Nina, et al.
Pubblicazione: (2026)

Deep Huber quantile regression networks
di: Tyralis, Hristos, et al.
Pubblicazione: (2023)

Multinomial belief networks for healthcare data
di: Donker, H. C., et al.
Pubblicazione: (2023)

Fairboard: a quantitative framework for equity assessment of healthcare models
di: Ruffle, James K., et al.
Pubblicazione: (2026)

An unified approach to link prediction in collaboration networks
di: Sosa, Juan, et al.
Pubblicazione: (2024)

A Statistical Framework for Spatial Boundary Estimation and Change Detection: Application to the Sahel Sahara Climate Transition
di: Tivenan, Stephen, et al.
Pubblicazione: (2025)

Resource-Based Time and Cost Prediction in Project Networks: From Statistical Modeling to Graph Neural Networks
di: Mirjalili, Reza, et al.
Pubblicazione: (2025)

Modeling Headway in Heterogeneous and Mixed Traffic Flow: A Statistical Distribution Based on a General Exponential Function
di: Leungbootnak, Natchaphon, et al.
Pubblicazione: (2025)

Enhancing convolutional neural network generalizability via low-rank weight approximation
di: Gao, Chenyin, et al.
Pubblicazione: (2022)

Time-Series Anomaly Classification for Launch Vehicle Propulsion Systems: Fast Statistical Detectors Enhancing LSTM Accuracy and Data Quality
di: Engelstad, Sean P., et al.
Pubblicazione: (2026)

Modeling Parkinson's Disease Progression Using Longitudinal Voice Biomarkers: A Comparative Study of Statistical and Neural Mixed-Effects Models
di: Tong, Ran, et al.
Pubblicazione: (2025)

Do Large Language Models (Really) Need Statistical Foundations?
di: Su, Weijie
Pubblicazione: (2025)

A Comprehensive Approach to Carbon Dioxide Emission Analysis in High Human Development Index Countries using Statistical and Machine Learning Techniques
di: Khosravi, Hamed, et al.
Pubblicazione: (2024)

meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
di: Sutariya, Dishantkumar, et al.
Pubblicazione: (2025)

DiffKnock: Diffusion-based Knockoff Statistics for Neural Networks Inference
di: Ge, Heng, et al.
Pubblicazione: (2025)

Improved generalization with deep neural operators for engineering systems: Path towards digital twin
di: Kobayashi, Kazuma, et al.
Pubblicazione: (2023)

Bayesian Bell regression model for fitting of overdispersed count data with application
di: Alhseeni, Ameer Musa Imran, et al.
Pubblicazione: (2024)

Conditional diffusions for amortized neural posterior estimation
di: Chen, Tianyu, et al.
Pubblicazione: (2024)

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
di: Imai, Kosuke, et al.
Pubblicazione: (2022)

An engine to simulate insurance fraud network data
di: Campo, Bavo D. C., et al.
Pubblicazione: (2023)

Tackling water table depth modeling via machine learning: From proxy observations to verifiability
di: Janssen, Joseph, et al.
Pubblicazione: (2024)

Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets
di: Jonker, Marianne A., et al.
Pubblicazione: (2023)

High-dimensional Statistics Applications to Batch Effects in Metabolomics
di: Guo, Zhendong
Pubblicazione: (2024)

A Statistical Theory of Regularization-Based Continual Learning
di: Zhao, Xuyang, et al.
Pubblicazione: (2024)

Variable importance measure for spatial machine learning models with application to air pollution exposure prediction
di: Cheng, Si, et al.
Pubblicazione: (2024)