Results 51 to 60 of about 11,198,121 (288)

Physics-informed machine learning as a kernel method

CoRR
L'apprentissage automatique informé par la physique combine l'expressivité des approches basées sur les données avec l'interprétabilité des modèles physiques. Dans ce contexte, nous considérons un problème de régression où le risque empirique est régularisé par une équation aux dérivées partielles (EDP) qui quantifie l'incohérence physique.
Doumèche, Nathan, Bach, Francis, Biau, Gérard, Boyer, Claire   +3 more
openaire   +4 more sources

Soft motions encoded by the fold and mediated by conserved hinge sites drive V‐ATPase allosteric machinery and autoinhibition

FEBS Letters, EarlyView.
Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana, Xiaowei Bogetti, Stuti Sharma, Ivet Bahar   +3 more
wiley   +1 more source

Physics-informed machine learning for metamodeling thermal comfort in non-air-conditioned buildings

, 2023
International audienceThere is a growing need for accurate and interpretable machine learning models of thermal comfort in buildings. Physics-informed machine learning could address this need by adding physical consistency to such models.
Jaffal, Issa
core   +1 more source

From Data to Physics: Physics-Informed Machine Learning Frameworks in Interdisciplinary Applications

Dynamics
Computational modeling and machine learning have impacted several different areas of science and accelerated advancements in multiple venues. Yet traditional machine learning models have many well-known drawbacks: besides demanding a significant amount ...
Carlos A. Valentim, Sergio A. David
doaj   +1 more source

The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection

Molecular Oncology, EarlyView.
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński, Krzysztof Pastuszak, Anna Samelak‐Czajka, Zuzanna Cemka, Paulina Jackowiak, Tomasz Stefaniak, Sylwia Łapińska‐Szumczyk, Jacek Jassem, Anna J. Żaczek, Matthew T. Rondina, Myron G. Best, Sjors G. J. G. In 't Veld, Anna Supernat   +12 more
wiley   +1 more source

Uncovering Drone Intentions using Control Physics Informed Machine Learning: data

This repository provides the data and code of the paper "Uncovering Drone Intentions using Control Physics Informed Machine ...
Adolfo Perrusquia Guzman (10429466), Weisi Guo (7451489), Zhuangkun Wei (10811460), Benjamin Fraser (18075975)   +3 more
core   +2 more sources

Integrating machine learning and physics-based modeling for predictive design of gemcitabine-loaded nanocomposites

Scientific Reports
This study aims to develop a machine learning framework to predict loading efficiency and encapsulation efficiency in gemcitabine-loaded nanocomposites, thereby overcoming the limitations of purely experimental approaches.
Abbas Rahdar, Sonia Fathi-karkan, Maryam Shirzad   +2 more
doaj   +1 more source

Safe Physics-informed Machine Learning for Dynamics and Control

2025 American Control Conference (ACC)
This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models and safety guarantees. As machine learning techniques enhance the modeling and control of complex dynamical systems, ensuring safety and stability remains a critical ...
Ján Drgona, Truong X. Nghiem, Thomas Beckers 0001, Mahyar Fazlyab, Enrique Mallada, Colin N. Jones, Draguna L. Vrabie, Steven L. Brunton, Rolf Findeisen   +8 more
openaire   +4 more sources

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Report and recommendations on multimedia materials for teaching and learning quantum physics [PDF]

, 2015
An international collaboration of physicists, affiliated with Multimedia Physics for Teaching and Learning (MPTL) and MERLOT, performed a survey and review of multimedia-based learning materials for quantum physics and quantum mechanics.
Mason, B, Silva, J, Santi, L, Kohnle, A, Melder, T, Girwidz, R, Dębowska, E, Arpornthip, T, Greczyło, T, Michelini, M   +9 more
core   +1 more source