Zobrazeno 61 - 70
of 62 732
pro vyhledávání: '"Metz, TO"'
Autor:
Hannah Preßler, Marie-Luise Machule, Friederike Ufer, Isabel Bünger, Lucie Yuanting Li, Emilie Buchholz, Claudia Werner, Esther Beraha, Frank Wagner, Matthes Metz, Susen Burock, Lisa Bruckert, Christiana Franke, Nicola Wilck, Anne Krüger, Alexander Reshetnik, Kai-Uwe Eckardt, Matthias Endres, Harald Prüss
Publikováno v:
Trials, Vol 25, Iss 1, Pp 1-16 (2024)
Abstract Background Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severely debilitating condition which markedly restricts activity and function of affected people. Since the beginning of the COVID-19 pandemic ME/CFS related to pos
Externí odkaz:
https://doaj.org/article/51c103a436324f498fc1f7027c245b1c
Autor:
Metz, Luke, Harrison, James, Freeman, C. Daniel, Merchant, Amil, Beyer, Lucas, Bradbury, James, Agrawal, Naman, Poole, Ben, Mordatch, Igor, Roberts, Adam, Sohl-Dickstein, Jascha
While deep learning models have replaced hand-designed features across many domains, these models are still trained with hand-designed optimizers. In this work, we leverage the same scaling approach behind the success of deep learning to learn versat
Externí odkaz:
http://arxiv.org/abs/2211.09760
Autor:
Lu, Chris, Kuba, Jakub Grudzien, Letcher, Alistair, Metz, Luke, de Witt, Christian Schroeder, Foerster, Jakob
Tremendous progress has been made in reinforcement learning (RL) over the past decade. Most of these advancements came through the continual development of new algorithms, which were designed using a combination of mathematical derivations, intuition
Externí odkaz:
http://arxiv.org/abs/2210.05639
Autor:
Bykovets, Eugene, Metz, Yannick, El-Assady, Mennatallah, Keim, Daniel A., Buhmann, Joachim M.
While deep reinforcement learning (RL) agents have showcased strong results across many domains, a major concern is their inherent opaqueness and the safety of such systems in real-world use cases. To overcome these issues, we need agents that can qu
Externí odkaz:
http://arxiv.org/abs/2210.03649
Learned optimizers -- neural networks that are trained to act as optimizers -- have the potential to dramatically accelerate training of machine learning models. However, even when meta-trained across thousands of tasks at huge computational expense,
Externí odkaz:
http://arxiv.org/abs/2209.11208
Autor:
Silva, Jeferson D., Metz, Fernando L.
The spectral and localization properties of heterogeneous random graphs are determined by the resolvent distributional equations, which have so far resisted an analytic treatment. We solve analytically the resolvent equations of random graphs with an
Externí odkaz:
http://arxiv.org/abs/2209.06805
Autor:
Tung, Karine, De La Torre, Steven, Mistiri, Mohamed El, De Braganca, Rebecca Braga, Hekler, Eric, Pavel, Misha, Rivera, Daniel, Klasnja, Pedja, Spruijt-Metz, Donna, Marlin, Benjamin M.
In this paper we present BayesLDM, a system for Bayesian longitudinal data modeling consisting of a high-level modeling language with specific features for modeling complex multivariate time series data coupled with a compiler that can produce optimi
Externí odkaz:
http://arxiv.org/abs/2209.05581
Autor:
Bhattacharya, Shohini, Cichy, Krzysztof, Constantinou, Martha, Dodson, Jack, Gao, Xiang, Metz, Andreas, Mukherjee, Swagato, Scapellato, Aurora, Steffens, Fernanda, Zhao, Yong
Traditionally, lattice QCD computations of generalized parton distributions (GPDs) have been carried out in a symmetric frame, where the transferred momentum is symmetrically distributed between the incoming and outgoing hadrons. However, such frames
Externí odkaz:
http://arxiv.org/abs/2209.05373
Autor:
Fletcher Metz, Abigail M. Olsen, Fachuang Lu, Kevin S. Myers, Marco N. Allemann, Joshua K. Michener, Daniel R. Noguera, Timothy J. Donohue
Publikováno v:
mBio, Vol 15, Iss 8 (2024)
ABSTRACT Aromatic compounds are an important source of commodity chemicals traditionally produced from fossil fuels. Aromatics derived from plant lignin can potentially be converted into commodity chemicals through depolymerization followed by microb
Externí odkaz:
https://doaj.org/article/c742738cc31a48cfad29d6fba750e69f
Autor:
Nicholas C. Castro, Jimmie Bullock, Katarzyna Haynesworth, Sarah Loftus, Jordan Metz, Hayley North, Troy J. Kemp, Ligia A. Pinto
Publikováno v:
Heliyon, Vol 10, Iss 14, Pp e34449- (2024)
SARS-CoV-2 serology plays a crucial role in assessing COVID-19 vaccine immunogenicity and antibody responses to SARS-CoV-2 infection. Tube type and anticoagulant may influence serology results. Thus, understanding the influence of these variables in
Externí odkaz:
https://doaj.org/article/0a8ab8c4919c4742abc6997cc09d8c2e