Suchergebnisse - "Bayesian algorithm execution"

Targeted materials discovery using Bayesian algorithm execution

Autoren: Sathya R. Chitturi Akash Ramdas Yue Wu et al.

Quelle: npj Computational Materials, Vol 10, Iss 1, Pp 1-12 (2024)

Schlagwörter: Materials of engineering and construction. Mechanics of materials, TA401-492, Computer software, QA76.75-76.765

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2057-3960

Zugangs-URL: https://doaj.org/article/392b6cf994d2442fa62f48bcd95108a5

Practical Bayesian Algorithm Execution via Posterior Sampling

Autoren: Cheng, Chu Xin Astudillo, Raul Desautels, Thomas et al.

Index Begriffe: Computer Science - Machine Learning, Mathematics - Optimization and Control, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2410.20596

Efficient Dynamic and Momentum Aperture Optimization for Lattice Design Using Multipoint Bayesian Algorithm Execution

Autoren: Zhang, Z. Agapov, I. Gasiorowski, S. et al.

Schlagwörter: Accelerator Physics, Machine Learning

Relation: http://arxiv.org/abs/2511.17850

Verfügbarkeit: http://arxiv.org/abs/2511.17850

Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution

Autoren: Moosbauer, Julia Casalicchio, Giuseppe Lindauer, Marius et al.

Index Begriffe: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2206.05447

Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information

Autoren: Neiswanger, Willie Wang, Ke Alexander Ermon, Stefano

Index Begriffe: Statistics - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Information Theory, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/2104.09460

Autonomous beam alignment through quadrupole triplets using Bayesian Algorithm Execution

Autoren: Roussel,Ryan Kennedy,Dylan Wisniewski,Eric et al.

Schlagwörter: mc4-technology - MC4: Technology, MC4.5 - MC4.5 Other technology, Accelerator Physics

Targeted materials discovery using Bayesian algorithm execution.

Autoren: Chitturi, Sathya R. Ramdas, Akash Wu, Yue et al.

Quelle: NPJ Computational Materials; 7/18/2024, Vol. 10 Issue 1, p1-12, 12p

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

Autoren: Sara Ayoub Miskovich Willie Neiswanger William Colocho et al.

Quelle: Machine Learning: Science and Technology, Vol 5, Iss 1, p 015004 (2024)

Schlagwörter: online optimization, multipoint optimization, particle accelerator, x-ray free electron laser, Bayesian optimization, Bayesian algorithm execution, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Relation: https://doi.org/10.1088/2632-2153/ad169f; https://doaj.org/toc/2632-2153; https://doaj.org/article/16c8837fd6fe43389e1ad5c9584b3d4a

Verfügbarkeit: https://doi.org/10.1088/2632-2153/ad169f
https://doaj.org/article/16c8837fd6fe43389e1ad5c9584b3d4a

Time-series generative networks for synthesizing realistic scenarios in occupant-centric building simulation.

Autoren: Chakrabarty, Ankush Vanfretti, Luigi Wang, Ye et al.

Quelle: Building Simulation; Aug2025, Vol. 18 Issue 8, p2115-2133, 19p

Materials design with target-oriented Bayesian optimization.

Autoren: Tian, Yuan Li, Tongtong Pang, Jianbo et al.

Quelle: NPJ Computational Materials; 7/3/2025, Vol. 11 Issue 1, p1-11, 11p

Schlagwörter: VALUATION of real property, SAMPLING methods

Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives

Autoren: Miskovich, Sara A. Neiswanger, Willie Colocho, William et al.

Index Begriffe: Physics - Accelerator Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2209.04587

Bayesian optimization of biodegradable polymers via machine learning driven features from low-field NMR data.

Autoren: Fujita, Ryo Amamoto, Yoshifumi Kikuchi, Jun

Quelle: NPJ Materials Degradation; 6/18/2025, Vol. 9 Issue 1, p1-9, 9p

Schlagwörter: CONVOLUTIONAL neural networks, NUCLEAR magnetic resonance, POLYLACTIC acid, MACHINE learning, VALUATION of real property

Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning.

Autoren: Wenjian Guo Fayuan Li Lingyu Wang et al.

Quelle: Advanced Powder Materials; Jun2025, Vol. 4 Issue 3, p1-12, 12p

Schlagwörter: ULTRA-high-temperature ceramics, GENERATIVE adversarial networks, DATA augmentation, MACHINE learning, MATERIALS science, MICROSTRUCTURE, CHEMICAL reactions

Materials-discovery workflow guided by symbolic regression for identifying acid-stable oxides for electrocatalysis.

Autoren: Nair, Akhil S. Foppa, Lucas Scheffler, Matthias

Quelle: NPJ Computational Materials; 5/26/2025, Vol. 11 Issue 1, p1-7, 7p

Schlagwörter: WATER use, WORKFLOW, ELECTROCATALYSIS, OXIDES, FORECASTING

Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty.

Autoren: Wei, Qinghua Wang, Yuanhao Yang, Guo et al.

Quelle: NPJ Computational Materials; 1/10/2025, Vol. 11 Issue 1, p1-14, 14p

Schlagwörter: LEAD-free solder, MACHINE learning, SOLDER & soldering, SOLDER joints, MULTI-objective optimization

Adaptive Optical Closed-Loop Control on the Basis of Hyperparametric Optimization of Convolutional Neural Networks.

Autoren: Chen, Bo Zhou, Yilin Jia, Jingjing et al.

Quelle: Applied Sciences (2076-3417); Aug2023, Vol. 13 Issue 15, p8589, 12p

Schlagwörter: WAVEFRONT sensors, CONVOLUTIONAL neural networks, ADAPTIVE optics, OPTICAL control, DEEP learning, LIGHT intensity

src47/materials-bax-gpflow: Paper Submission

Autoren: Chitturi, Sathya Ramdas, Akash Neiswanger, Willie

Relation: https://github.com/src47/materials-bax-gpflow/tree/v1; https://zenodo.org/records/10222982; oai:zenodo.org:10222982; https://doi.org/10.5281/zenodo.10222982

Verfügbarkeit: https://doi.org/10.5281/zenodo.10222982
https://zenodo.org/records/10222982

src47/multibax-sklearn

Autoren: Chitturi, Sathya Ramdas, Akash Neiswanger, Willie

Relation: https://github.com/src47/multibax-sklearn/tree/v1; https://zenodo.org/records/10233974; oai:zenodo.org:10233974; https://doi.org/10.5281/zenodo.10233974

Verfügbarkeit: https://doi.org/10.5281/zenodo.10233974
https://zenodo.org/records/10233974

ChristopherMayes/Xopt: Xopt v1.4.1

Autoren: Christopher Mayes Ryan Roussel Jacqueline Garrahan et al.

Relation: https://github.com/ChristopherMayes/Xopt/tree/v1.4.1; https://zenodo.org/records/7983779; oai:zenodo.org:7983779; https://doi.org/10.5281/zenodo.7983779

Verfügbarkeit: https://doi.org/10.5281/zenodo.7983779
https://zenodo.org/records/7983779

Human Development Report 2025 : A Matter of Choice: People and Possibilities in the Age of AI

Autoren: United Nations Development Programme (UNDP)

Resource Type: eBook.

Categories: COMPUTERS / Artificial Intelligence / General, POLITICAL SCIENCE / International Relations / General, POLITICAL SCIENCE / Public Policy / General