Results 131 to 140 of about 8,838,426 (323)
Shield Machine Attitude Prediction Method Based on Causal Graph Convolutional Network
Accurately predicting and controlling the attitude of a shield tunneling machine is critical for quality assurance in shield tunneling projects. Existing prediction methods utilize historical data to construct a machine learning framework to predict ...
Liang Zeng +4 more
doaj +1 more source
What Do Large Language Models Know About Materials?
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 +2 more
wiley +1 more source
Towards a Theory of Representation Learning for Reinforcement Learning
Presented online via Bluejeans Events on September 15, 2021 at 12:15 p.m.Alekh Agarwal is a researcher who works on theoretical foundations of machine learning, spanning many areas including large-scale and distributed optimization, high-dimensional ...
Agarwal, Alekh
core
Video-Language Critic : Transferable Reward Functions for Language-Conditioned Robotics [PDF]
Publisher Copyright: © 2025, Transactions on Machine Learning Research.Natural language is often the easiest and most convenient modality for humans to specify tasks for robots.
Woungang, Isaac +6 more
core +1 more source
Genetic programming and deductive-inductive learning: a multistrategy approach [PDF]
Proceedings of: 15th International Conference on Machine Learning, Madison (Wisconsin, USA), July 24-27, 1998.Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions ...
Borrajo, Daniel +5 more
core +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
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 +2 more
wiley +1 more source
Decentralized blockchain governance for explainable causal AI in macroeconomic forecasting
The increasing occurrence of structural breaks, financial crises, and economic uncertainty has significantly weakened the predictive performance of traditional macroeconomic forecasting models.
Oumaima Abouzaid, Faouzi Boussedra
doaj +1 more source
Essays on using machine learning for causal inference
Um Daten am effektivsten zu nutzen, muss die moderne Ökonometrie ihren Werkzeugkasten an Modellen erweitern und neu denken. Das Feld, in dem diese Transformation am besten beobachtet werden kann, ist die kausale Inferenz. Diese Dissertation verfolgt die Absicht Probleme zu untersuchen, Lösungen zu präsentieren und neue Methoden zu entwickeln Machine ...
openaire +2 more sources
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source

