Thermodynamics à la Souriau on Kähler Non-Compact Symmetric Spaces for Cartan Neural Networks. [PDF]
Fré PG, Sorin AS, Trigiante M.
europepmc +1 more source
A tandem neural network directly solves the multivalued inverse problem of extracting semiconductor parameters from transistor measurements. Trained on only 1000 simulations, the network infers six material parameters (e.g., defect states, carrier concentration, mobility) in under 1 ms, demonstrating a broadly applicable framework for semiconductor ...
Masatoshi Kimura +8 more
wiley +1 more source
Precise Time Synchronization in Packet Networks Using Deep Learning for Future Intelligent Transportation. [PDF]
Deng H, Li H, Tian Z, Tian J, Du W.
europepmc +1 more source
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
A shared frailty model for assessing time to seizure remission in adults with epilepsy. [PDF]
Jote AD, Lelisho ME, Sheferaw WE.
europepmc +1 more source
ABSTRACT Maintaining an effective balance between exploration and exploitation is essential during optimization processes, from mathematical functions to more complex problems such as constrained engineering design optimization, particularly when addressing highly nonlinear issues with numerous local optima and strict feasibility requirements.
Enrique Lizárraga +3 more
wiley +1 more source
A Proposal for Homoskedastic Modeling With Conditional Auto-Regressive Distributions. [PDF]
Martinez-Beneito MA +3 more
europepmc +1 more source
Input Layer Regularization and Automated Regularization Hyperparameter Tuning for Myelin Water Estimation Using Deep Learning. [PDF]
Modi M +7 more
europepmc +1 more source
Childhood underweight in Ethiopia: modelling non-linear risk factors and geographic hotspots using Bayesian geoadditive methods. [PDF]
Derso EA, Campolo MG, Alibrandi A.
europepmc +1 more source
Accelerating Sustainable Epoxy Resin Development Through Bayesian Optimization and Inverse Design
Development of a machine learning framework for the optimization of the Tg of partially bio‐based epoxy resin formulations in a 13‐component design space using Bayesian optimization, active learning, random design, and inverse design. The results show that the BO effectively navigates high‐dimensional formulation spaces, and the final ML model could ...
Natalie Wunder +3 more
wiley +1 more source

