Zobrazeno 1 - 10
of 16 163
pro vyhledávání: '"A. Scher"'
Autor:
Kowald, Dominik, Scher, Sebastian, Pammer-Schindler, Viktoria, Müllner, Peter, Waxnegger, Kerstin, Demelius, Lea, Fessl, Angela, Toller, Maximilian, Estrada, Inti Gabriel Mendoza, Simic, Ilija, Sabol, Vedran, Truegler, Andreas, Veas, Eduardo, Kern, Roman, Nad, Tomislav, Kopeinik, Simone
Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable outcomes or have been used in questionable manners. As a result, there ha
Externí odkaz:
http://arxiv.org/abs/2411.09973
Autor:
Cody, Sean Enis, Scher, Sebastian, McDonald, Iain, Zijlstra, Albert, Alexander, Emma, Cox, Nick L. J.
Publikováno v:
Open Research Europe 4, no. 29 (2024): 29
Identifying stars belonging to different classes is vital in order to build up statistical samples of different phases and pathways of stellar evolution. In the era of surveys covering billions of stars, an automated method of identifying these class
Externí odkaz:
http://arxiv.org/abs/2410.22869
The escape dynamics of sticky particles from textured surfaces is poorly understood despite importance to various scientific and technological domains. In this work, we address this challenge by investigating the escape time of adsorbates from preval
Externí odkaz:
http://arxiv.org/abs/2401.05227
Adsorption to a surface, reversible-binding, and trapping are all prevalent scenarios where particles exhibit "stickiness". Escape and first-passage times are known to be drastically affected, but detailed understanding of this phenomenon remains ill
Externí odkaz:
http://arxiv.org/abs/2305.08701
Ensuring Reliable Robot Task Performance through Probabilistic Rare-Event Verification and Synthesis
Providing guarantees on the safe operation of robots against edge cases is challenging as testing methods such as traditional Monte-Carlo require too many samples to provide reasonable statistics. Built upon recent advancements in rare-event sampling
Externí odkaz:
http://arxiv.org/abs/2304.14886
For a long time, machine learning (ML) has been seen as the abstract problem of learning relationships from data independent of the surrounding settings. This has recently been challenged, and methods have been proposed to include external constraint
Externí odkaz:
http://arxiv.org/abs/2302.03361
Publikováno v:
Revista Brasileira de Zootecnia, Vol 40, Iss 4, Pp 821-826 (2011)
Este trabalho foi realizado com o objetivo de avaliar o desempenho produtivo de matrizes de corte submetidas a dietas contendo aflatoxinas e adsorvente à base de glucomananos esterificados. Foram utilizados 300 fêmeas e 40 machos da linhagem Ross 3
Externí odkaz:
https://doaj.org/article/80e2f34249fa4e20a3219e7ce612355f
Gated first-passage processes, where completion depends on both hitting a target and satisfying additional constraints, are prevalent across various fields. Despite their significance, analytical solutions to basic problems remain unknown, e.g. the d
Externí odkaz:
http://arxiv.org/abs/2211.09164
Publikováno v:
Phys. Rev. Research 5, L032043 (2023)
First-passage times provide invaluable insight into fundamental properties of stochastic processes. Yet, various forms of gating mask first-passage times and differentiate them from actual detection times. For instance, imperfect conditions may inter
Externí odkaz:
http://arxiv.org/abs/2210.00678
Autor:
Schweimer, Christoph, Scher, Sebastian
The concept of trustworthy AI has gained widespread attention lately. One of the aspects relevant to trustworthy AI is robustness of ML models. In this study, we show how to probabilistically quantify robustness against naturally occurring distortion
Externí odkaz:
http://arxiv.org/abs/2208.10354