Results 81 to 90 of about 29,055 (302)

An Ordinal Shapley Value for Economic Environments (Revised Version) [PDF]

We propose a new solution concept to address the problem of sharing a surplus among the agents generating it. The problem is formulated in the preferences-endowments space.
David Wettstein, David Perez-Castrillo
core  

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

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  

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

A Machine Learning Model for Predicting Posthepatectomy Liver Failure After Hepatectomy With Extrahepatic Bile Duct Resection for Perihilar Cholangiocarcinoma: With and Without Indocyanine Green

Annals of Gastroenterological Surgery, EarlyView.
Using machine learning‐based decision tree models, patients with perihilar cholangiocarcinoma undergoing major hepatectomy with extrahepatic bile duct resection were stratified according to the risk of posthepatectomy liver failure. Separate models were developed with and without indocyanine green data, enabling clinically interpretable preoperative ...
Yuki Homma, Hiroki Ohya, Ryusei Matsuyama, Isamu Hosokawa, Tsukasa Takayashiki, Yusuke Ome, Shuichiro Uemura, Ryota Higuchi, Goro Honda, Eiryo Kawakami, Masayuki Ohtsuka, Itaru Endo   +11 more
wiley   +1 more source

On Using the Shapley Value for Anomaly Localization: A Statistical Investigation

Applied AI Letters
Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. We use a reasonable statistical model for the classifiers required to compute the Shapley value to provide repeatable and rigorous analysis in ...
Rick S. Blum, Xubin Fang, Franziska Freytag   +2 more
doaj   +1 more source

Dynamic evaluation and realization mechanisms of multi-dimensional benefits for microgrids in new-type power systems

Frontiers in Energy Research
Amid high renewable penetration, market reform, and dual-carbon goals, microgrids are expected to deliver economic, environmental, and technical value, yet much work remains static or single-dimensional and lacks a closed loop from evaluation to fair ...
Zhengdong Wan, Jinsong Zhang, Yan Huang
doaj   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

SWTA-Shapley: an efficient contribution evaluation method for federated learning

Dianxin kexue
Federated learning has effectively addressed the “data silo” issue caused by data privacy protection. To maintain the long-term operation of federated learning systems, it is necessary to attract high-quality data owners to participate in federated ...
BAO Shihao, NI Zhengwei
doaj