Zobrazeno 1 - 10
of 3 887
pro vyhledávání: '"Kalthoff IS"'
Autor:
Cheng, Austin, Ser, Cher Tian, Skreta, Marta, Guzmán-Cordero, Andrés, Thiede, Luca, Burger, Andreas, Aldossary, Abdulrahman, Leong, Shi Xuan, Pablo-García, Sergio, Strieth-Kalthoff, Felix, Aspuru-Guzik, Alán
Publikováno v:
Faraday Discuss., 2024
Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspecti
Externí odkaz:
http://arxiv.org/abs/2409.10304
Autor:
Wang, Haorui, Skreta, Marta, Ser, Cher-Tian, Gao, Wenhao, Kong, Lingkai, Strieth-Kalthoff, Felix, Duan, Chenru, Zhuang, Yuchen, Yu, Yue, Zhu, Yanqiao, Du, Yuanqi, Aspuru-Guzik, Alán, Neklyudov, Kirill, Zhang, Chao
Molecular discovery, when formulated as an optimization problem, presents significant computational challenges because optimization objectives can be non-differentiable. Evolutionary Algorithms (EAs), often used to optimize black-box objectives in mo
Externí odkaz:
http://arxiv.org/abs/2406.16976
Autor:
Kristiadi, Agustinus, Strieth-Kalthoff, Felix, Subramanian, Sriram Ganapathi, Fortuin, Vincent, Poupart, Pascal, Pleiss, Geoff
Bayesian optimization (BO) is an integral part of automated scientific discovery -- the so-called self-driving lab -- where human inputs are ideally minimal or at least non-blocking. However, scientists often have strong intuition, and thus human fee
Externí odkaz:
http://arxiv.org/abs/2406.06459
Autor:
Kristiadi, Agustinus, Strieth-Kalthoff, Felix, Skreta, Marta, Poupart, Pascal, Aspuru-Guzik, Alán, Pleiss, Geoff
Automation is one of the cornerstones of contemporary material discovery. Bayesian optimization (BO) is an essential part of such workflows, enabling scientists to leverage prior domain knowledge into efficient exploration of a large molecular space.
Externí odkaz:
http://arxiv.org/abs/2402.05015
Autor:
Stefan Lohse, Jan Niklas Mink, Lea Eckhart, Muriel Charlotte Hans, Leuart Jusufi, Anabel Zwick, Tobias Mohr, Isabelle Ariane Bley, Oybek Khalmurzaev, Vsevolod Borisovich Matveev, Philine Loertzer, Alexey Pryalukhin, Arndt Hartmann, Carol-Immanuel Geppert, Hagen Loertzer, Heiko Wunderlich, Hans-Peter Lenhof, Carsten Maik Naumann, Holger Kalthoff, Kerstin Junker
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract PeCa is a rare entity with rising incidence rates due to increased infections with human papillomaviruses (HPV). The distinct subtypes of PeCa with an individual pathogenesis demand biomarkers for a precise patient risk assessment regarding
Externí odkaz:
https://doaj.org/article/44685576c60d4956a0b1b1ae91aa2404
Autor:
Sandra Kalthoff, Caroline Wolniak, Philipp Lutz, Christian P. Strassburg, Bettina Langhans, Leona Dold
Publikováno v:
BMC Gastroenterology, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Primary sclerosing cholangitis (PSC) is a chronic liver disease leading to inflammation with scaring and strictures of bile ducts, which can lead to liver cirrhosis. A subtype of PSC characterized by high serum IgG4 (sIgG4) levels
Externí odkaz:
https://doaj.org/article/17f2e98fb6224e8b8c65c9a71b1bab13
Autor:
Griffiths, Ryan-Rhys, Klarner, Leo, Moss, Henry B., Ravuri, Aditya, Truong, Sang, Stanton, Samuel, Tom, Gary, Rankovic, Bojana, Du, Yuanqi, Jamasb, Arian, Deshwal, Aryan, Schwartz, Julius, Tripp, Austin, Kell, Gregory, Frieder, Simon, Bourached, Anthony, Chan, Alex, Moss, Jacob, Guo, Chengzhi, Durholt, Johannes, Chaurasia, Saudamini, Strieth-Kalthoff, Felix, Lee, Alpha A., Cheng, Bingqing, Aspuru-Guzik, Alán, Schwaller, Philippe, Tang, Jian
We introduce GAUCHE, a library for GAUssian processes in CHEmistry. Gaussian processes have long been a cornerstone of probabilistic machine learning, affording particular advantages for uncertainty quantification and Bayesian optimisation. Extending
Externí odkaz:
http://arxiv.org/abs/2212.04450
Autor:
Baykusheva, Denitsa R., Kalthoff, Mona H., Hofmann, Damian, Claassen, Martin, Kennes, Dante M., Sentef, Michael A., Mitrano, Matteo
Publikováno v:
Phys. Rev. Lett. 130, 106902, (2023)
Many-body entanglement in condensed matter systems can be diagnosed from equilibrium response functions through the use of entanglement witnesses and operator-specific quantum bounds. Here, we investigate the applicability of this approach for detect
Externí odkaz:
http://arxiv.org/abs/2209.02081
Publikováno v:
Weather and Climate Dynamics, Vol 5, Pp 609-631 (2024)
Over heterogeneous, mountainous terrain, the determination of spatial heterogeneity of any type of a turbulent layer has been known to pose substantial challenges in mountain meteorology. In addition to the combined effect in which buoyancy and shear
Externí odkaz:
https://doaj.org/article/a7ae8d667d51429ca75ca89cafb51df2
Autor:
Krenn, Mario, Ai, Qianxiang, Barthel, Senja, Carson, Nessa, Frei, Angelo, Frey, Nathan C., Friederich, Pascal, Gaudin, Théophile, Gayle, Alberto Alexander, Jablonka, Kevin Maik, Lameiro, Rafael F., Lemm, Dominik, Lo, Alston, Moosavi, Seyed Mohamad, Nápoles-Duarte, José Manuel, Nigam, AkshatKumar, Pollice, Robert, Rajan, Kohulan, Schatzschneider, Ulrich, Schwaller, Philippe, Skreta, Marta, Smit, Berend, Strieth-Kalthoff, Felix, Sun, Chong, Tom, Gary, von Rudorff, Guido Falk, Wang, Andrew, White, Andrew, Young, Adamo, Yu, Rose, Aspuru-Guzik, Alán
Publikováno v:
Cell Patterns 3(10), 100588(2022)
Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways,
Externí odkaz:
http://arxiv.org/abs/2204.00056