Concept

Scientific law

Related publications (53)

Sparse autoregressive neural networks for classical spin systems

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Lausanne2024

Learning Physics-Consistent Particle Interactions

Olga Fink, David Simon Kammer, Zhichao Han

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

Oxford University Press2023

Game changers in science and technology- now and beyond

The recent devastating pandemic has drastically reminded humanity of the importance of constant scientific and technological progress. A strong interdisciplinary dialogue between academic and industrial scientists of various specialties, entrepreneurs, man ...

ELSEVIER SCIENCE INC2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Olga Fink, Jian Zhou

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

2023

Generating Controlled Physics-Informed Time-to-failure Trajectories for Prognostics in Unseen Operational Conditions

Olga Fink, Jian Zhou

Research Publishing2023

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-Based Filters

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency between any known underlying physical laws and a data-driven decision-making process, preprocessin ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A hybrid microscopic model for multimodal traffic with empirical observations from aerial footage

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are neglected in lane-based traffic. In cities, as opposed to highways, this is an o ...

National Academies2023

The strength of surgical knots involves a critical interplay between friction and elastoplasticity

Pedro Miguel Nunes Pereira de Almeida Reis, Paul Johanns, Changyeob Baek, Paul Grandgeorge

Knots are the weakest link in surgical sutures, serving as mechanical ligatures between filaments. Exceeding their safe operational limits can cause fatal complications. The empirical nature of present guidelines calls for a predictive understanding of the ...

AMER ASSOC ADVANCEMENT SCIENCE2023

Scientific rewards for biomedical specialization are large and persistent

Gaétan Jean A de Rassenfosse, Orion B Penner, Kyle William Higham

Background While specialization plays an essential role in how scientific research is pursued, we understand little about its effects on a researcher's impact and career. In particular, the extent to which one specializes within their chosen fields likely ...

BMC2022

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