Showing 101 - 120 of 1,212

101

Transparent Serverless execution of Python multiprocessing applications
Arjona, Aitor ; Finol, Gerard ; Garcia-Lopez, Pedro ; et al.

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102

ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: Construction of supervised machine learning regression pipelines for livestock data modeling: A case study.
Tulpan D ; Tedeschi LO ; Menendez H ; et al.
Publisher: American Society of Animal Science Country of Publication: United States NLM ID: 8003002 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1525-3163 (Electronic) Linking ISSN: 00218812 NLM ISO Abbreviation: J Anim Sci Subsets: MEDLINE

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103

Aplikace strojového učení pro predikci odchodu zákazníků ; Application of machine learning for customer churn prediction
Hýbl, Jan ; Witzany, Jiří ; Palán, Luděk

AUC hyperparameter tuning precision machine learning classification recall
Dissertation/ Thesis
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104

Using Physics-Informed Neural Networks for Modeling Biological and Epidemiological Dynamical Systems.
Farea, Amer ; Yli-Harja, Olli ; Emmert-Streib, Frank
Mathematics (2227-7390). May2025, Vol. 13 Issue 10, p1664. 23p.

ORDINARY differential eq... PHYSICAL laws DYNAMICAL systems INVERSE problems BIOLOGICAL neural networ... DEEP learning
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105

Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features
Daniel Hilário da Silva ; Caio Tonus Ribeiro ; Leandro Rodrigues da Silva Souza ; et al.
Brazilian Archives of Biology and Technology, Vol 68 (2025)

medical diagnosis Parkinson's Disease machine learning voice signal PyCaret TP248.13-248.65
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106

COMBO: An efficient Bayesian optimization library for materials science
Ueno, Tsuyoshi ; Rhone, Trevor David ; Hou, Zhufeng ; et al.
In Materials Discovery June 2016 4:18-21

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107

Enhanced deep neural network with interaction features for corn seed yield prediction: uncovering agroecophysiological relationships.
Jahan, Mohsen ; Amiri, Mohammad-Behzad ; Nassiri-Mahallati, Mehdi
Discover Agriculture; 11/3/2025, Vol. 3 Issue 1, p1-15, 15p

SEED yield ARTIFICIAL neural networ... PLANT-soil relationships MACHINE learning PRECISION farming CORN
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108

High Performance Computing with Python - Libraries and Best Practices for Distributed Computing in Data Science Workflows
Hubweber, Michaela

FTW:0854 Distributed Computing Machine Learning Deep Learning SLURM Python
Dissertation/ Thesis
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109

EasyGeSe – a resource for benchmarking genomic prediction methods.
Quesada-Traver, Carles ; Ariza-Suarez, Daniel ; Studer, Bruno ; et al.
BMC Genomics. 10/24/2025, Vol. 26 Issue 1, p1-13. 13p.

MACHINE learning PREDICTION models MATHEMATICAL statistics DATA libraries BENCHMARKING (Management... DATA science
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110

Thermal-property profiles from well-logs in sedimentary rocks: a novel machine-learning-based prediction tool trained on physically modelled synthetic data.
Hosseini-Nasab, Seyed Mojtaba ; Mousavi, Seyed Hamid Reza ; Fuchs, Sven
Geophysical Journal International. Oct2025, Vol. 243 Issue 1, p1-36. 36p.

THERMAL diffusivity THERMAL conductivity MACHINE learning SPECIFIC heat capacity HEAT capacity
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111

Microstructural and tribological investigation of B4C-reinforced Al6061 composites: insights from SEM and wear analysis.
Beldar, Pankaj ; Kadbhane, Snehal ; Kavale, Prashant ; et al.
Journal of Engineering & Applied Science; 10/14/2025, Vol. 72 Issue 1, p1-24, 24p

BORON carbides WEAR resistance METALLIC composites AUTOMOTIVE engineering SCANNING electron micros... MATHEMATICAL optimizatio...
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112

Optimización bayesiana con multifidelidad para la búsqueda de hiperparámetros en algoritmos de aprendizaje por refuerzo
Martínez Martínez, Gonzalo ; Molina González, Martín ; Garrido Merchán, Eduardo
Archivo Digital UPM
Universidad Politécnica de Madrid

Informática Multifidelity optimizati... Hyperparameter tuning Optimización multifideli... Matemáticas Aprendizaje por refuerzo
Dissertation/ Thesis
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113

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114

Case Study IV: Tuned Reinforcement Learning (in Python)
Zaefferer, Martin ; Chandrasekaran, Sowmya
Hyperparameter Tuning for Machine and Deep Learning with R ; page 271-281 ; ISBN 9789811951695 9789811951701

Book
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115

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116

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization
Dumont, Vincent ; Garner, Casey ; Trivedi, Anuradha ; et al.

Information and Computin... Machine Learning Bioengineering
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118

EdgeTune: Inference-Aware Hyperparameter Tuning
Isabelly Rocha ; orcid:0000-0001-7636- ; Valerio Schiavoni

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119

Tuning Hyperparameters without Grad Students: Scaling up Bandit Optimisation
Kirthevasan Kandasamy

FOS: Psychology 170203 Knowledge Represe...
Dissertation/ Thesis
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120

FLAML: The Python Wizardry for Automated Machine Learning
T. Aditya Sai Srinivas ; M. Bharathi

FLAML, AutoML
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