Results 161 to 170 of about 3,330 (201)

From Light to Energy: Machine Learning Algorithms for Position and Energy Deposition Estimation in Scintillator-SiPM Detectors. [PDF]

Sensors (Basel)
Simhony Y, Segal A, Amrani O, Etzion E.
europepmc   +1 more source

Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches. [PDF]

Sci Rep
Hussain I, Ching KB, Uttraphan C, Tay KG, Noor A, Memon SA.   +5 more
europepmc   +1 more source

Personalized training model for 10 m air pistol through machine learning: a pilot study. [PDF]

Sci Rep
Diao S, Zhou T, Du Y.
europepmc   +1 more source

Deep learning-based gait phase detection using shank-mounted IMU data: Classification approach. [PDF]

PLoS One
Choi W, Choi MT.
europepmc   +1 more source

Diabetic retinopathy as the primary predictor of mild cognitive impairment in type 2 diabetes: Insights from machine learning models. [PDF]

PLoS One
Rhmari Tlemçani FZ, Aitlahbib F, Laidi S, Alidrissi N, Aasfara J, Elamari S, Chadli A, Motaib I.   +7 more
europepmc   +1 more source

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Automating hyperparameter optimization in geophysics with Optuna: A comparative study

Geophysical Prospecting
AbstractDeep learning has gained attraction amongst geophysicists for solving complex longstanding problems. Nevertheless, proper hyperparameter optimization methodologies remain critically underexplored in geophysical deep learning research. This paper attempts to first highlight the importance of hyperparameter optimization and then showcase two ...
Hussain Almarzooq
exaly   +2 more sources

Scaling Up Optuna: P2P Distributed Hyperparameters Optimization

Concurrency Computation Practice and Experience
ABSTRACT In machine learning (ML), hyperparameter optimization (HPO) is the process of choosing a tuple of values that ensures an efficient deployment and training of an AI model. In practice, HPO not only applies to ML tuning but can also be used to tune complex numerical simulations.
exaly   +2 more sources

Optuna-XGBoost porosity prediction for logging profiles of carbonate formations

2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)
Chongchong Yu
exaly   +3 more sources

Predicting scour depth in the presence of aprons using XGBoost-Optuna

Applied Soft Computing Journal
Mohammad Vaghefi, Chonoor Abdi, Masoud Ghodsian   +2 more
exaly   +2 more sources