Results 231 to 240 of about 1,076,580 (347)

Recovering from Selection Bias in Causal and Statistical Inference

, 2014
Elias Bareinboim, Jin Tian, Judea Pearl
openalex   +2 more sources

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

MACFIV: a novel framework for nonlinear causal inference in the body mass index-hypertension relationship with many weak and pleiotropic genetic instruments. [PDF]

Brief Bioinform
Chen D, Wang Y, Shi D, Cao Y, Hu YQ.
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Adaptive Sparsening and Smoothing of the Treatment Model for Longitudinal Causal Inference Using Outcome-Adaptive LASSO and Marginal Fused LASSO. [PDF]

Stat Med
Schnitzer ME, Talbot D, Liu Y, Berger D, Wang G, O'Loughlin J, Sylvestre MP, Ertefaie A.   +7 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Machine learning-enhanced causal inference of surgical decisions and rehabilitation strategies in traumatic brain injury. [PDF]

Front Neurol
Irankhah E, Pagare M, Chetla L, Shen J, Ul Alam MA, Wolkowicz KL.   +5 more
europepmc   +1 more source

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

Advanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar, Dhanadeep Dutta, G. Bharat Reddy   +2 more
wiley   +1 more source

Organic Electrochemical Transistor Channel Materials: Copolymerization Versus Physical Mixing of Glycolated and Alkoxylated Polymers

Advanced Functional Materials, EarlyView.
This work discusses the use of blended channel materials in OECTs. It explores how mixing glycolated and alkoxylated polymers in various ratios offers a simpler and more efficient route to tuning OECT properties. The performance of the polymer blends is compared to the corresponding copolymers, demonstrating similar OECT characteristics, swelling ...
Lize Bynens, Kaishuai Zhang, Priscila Cavassin, Arwin Goossens, Jochen Vanderspikken, Tania C. H. Castillo, Demetra Tsokkou, Adam Marks, Arianna Magni, Karrie Weaver, Laurence Lutsen, Sahika Inal, Koen Vandewal, Natalie Banerji, Wouter Maes   +14 more
wiley   +1 more source

Towards causal inference-based antidepressant selection with brain and blood biomarkers. [PDF]

Neuropsychopharmacology
Barac M, Grant CW, Toll R, Carmody T, Minhajuddin A, Fatt CC, Foster JA, Croarkin PE, Bobo WV, Jha MK, Athreya AP, Trivedi MH.   +11 more
europepmc   +1 more source