Results 131 to 140 of about 776,810 (287)

The Shapley value for bicooperative games [PDF]

The aim of the present paper is to study a one-point solution concept for bicooperative games. For these games introduced by Bilbao (2000), we define a one-point solution called the Shapley value, since this value can be interpreted in a similar way to ...
Nieves Jiménez, Jesús Mario Bilbao, Jorge Jesús López, Julio R. Fernández   +3 more
core  

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Catboost - SHapley Additive exPlanations (SHAP) car following model: Explaining model features in mixed traffic conditions

Multimodal Transportation
Car-following behavior is critical for traffic management, road design, and the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AVs).
Tianyang Cui, D. J. Wu, Zejiang Wang
doaj   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Predictive modeling of millet growth in pesticide- and vinasse-amended soils using SHAP regression interpretation

Scientific Reports
Soil contamination by persistent agrochemicals such as tebuthiuron (TB) and thiamethoxam (TX), together with the use of agroindustrial by-products like vinasse (VN), affects soil-plant interactions and crop development. This study evaluated the biometric
Yanca Araujo Frias, Bruno Rafael de Almeida Moreira, Thalia Silva Valério, Amanda Letícia dos Santos, Victor Hugo Cruz, Giuliano Mikael Tonelo Pincerato, Paulo Renato Matos Lopes   +6 more
doaj   +1 more source

Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations

Multimodal Transportation
Efficient management of traffic incidents is a focal point in traffic management, with direct implications for road safety, congestion, and the environment.
Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene   +8 more
doaj   +1 more source

Precision of Individual Shapley Value Explanations

, 2023
Shapley values are extensively used in explainable artificial intelligence (XAI) as a framework to explain predictions made by complex machine learning (ML) models.
Olsen, Lars Henry Berge
core  

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source