Zobrazeno 1 - 10
of 6 139
pro vyhledávání: '"Ament, A A"'
Autor:
Ament, Sebastian, Santorella, Elizabeth, Eriksson, David, Letham, Ben, Balandat, Maximilian, Bakshy, Eytan
Gaussian processes (GPs) are non-parametric probabilistic regression models that are popular due to their flexibility, data efficiency, and well-calibrated uncertainty estimates. However, standard GP models assume homoskedastic Gaussian noise, while
Externí odkaz:
http://arxiv.org/abs/2410.24222
A key task in AutoML is to model learning curves of machine learning models jointly as a function of model hyper-parameters and training progression. While Gaussian processes (GPs) are suitable for this task, na\"ive GPs require $\mathcal{O}(n^3m^3)$
Externí odkaz:
http://arxiv.org/abs/2410.09239
Publikováno v:
2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN)
This article proposes a novel fuzzy clustering based anomaly detection method for pump current time series of EDFA systems. The proposed change detection framework (CDF) strategically combines the advantages of entropy analysis (EA) and principle com
Externí odkaz:
http://arxiv.org/abs/2408.15268
Autor:
Rodriguez-Fernandez, P., Howard, N. T., Saltzman, A., Kantamneni, S., Candy, J., Holland, C., Balandat, M., Ament, S., White, A. E.
This work presents the PORTALS framework, which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no lo
Externí odkaz:
http://arxiv.org/abs/2312.12610
Expected Improvement (EI) is arguably the most popular acquisition function in Bayesian optimization and has found countless successful applications, but its performance is often exceeded by that of more recent methods. Notably, EI and its variants,
Externí odkaz:
http://arxiv.org/abs/2310.20708
Eight percent of global carbon dioxide emissions can be attributed to the production of cement, the main component of concrete, which is also the dominant source of CO2 emissions in the construction of data centers. The discovery of lower-carbon conc
Externí odkaz:
http://arxiv.org/abs/2310.18288
Autor:
Chang, Ming-Chiang, Ament, Sebastian, Amsler, Maximilian, Sutherland, Duncan R., Zhou, Lan, Gregoire, John M., Gomes, Carla P., van Dover, R. Bruce, Thompson, Michael O.
X-ray diffraction (XRD) is an essential technique to determine a material's crystal structure in high-throughput experimentation, and has recently been incorporated in artificially intelligent agents in autonomous scientific discovery processes. Howe
Externí odkaz:
http://arxiv.org/abs/2308.07897
Autor:
Deshwal, Aryan, Ament, Sebastian, Balandat, Maximilian, Bakshy, Eytan, Doppa, Janardhan Rao, Eriksson, David
We consider the problem of optimizing expensive black-box functions over high-dimensional combinatorial spaces which arises in many science, engineering, and ML applications. We use Bayesian Optimization (BO) and propose a novel surrogate modeling ap
Externí odkaz:
http://arxiv.org/abs/2303.01774
Autor:
M. Wendisch, S. Crewell, A. Ehrlich, A. Herber, B. Kirbus, C. Lüpkes, M. Mech, S. J. Abel, E. F. Akansu, F. Ament, C. Aubry, S. Becker, S. Borrmann, H. Bozem, M. Brückner, H.-C. Clemen, S. Dahlke, G. Dekoutsidis, J. Delanoë, E. De La Torre Castro, H. Dorff, R. Dupuy, O. Eppers, F. Ewald, G. George, I. V. Gorodetskaya, S. Grawe, S. Groß, J. Hartmann, S. Henning, L. Hirsch, E. Jäkel, P. Joppe, O. Jourdan, Z. Jurányi, M. Karalis, M. Kellermann, M. Klingebiel, M. Lonardi, J. Lucke, A. E. Luebke, M. Maahn, N. Maherndl, M. Maturilli, B. Mayer, J. Mayer, S. Mertes, J. Michaelis, M. Michalkov, G. Mioche, M. Moser, H. Müller, R. Neggers, D. Ori, D. Paul, F. M. Paulus, C. Pilz, F. Pithan, M. Pöhlker, V. Pörtge, M. Ringel, N. Risse, G. C. Roberts, S. Rosenburg, J. Röttenbacher, J. Rückert, M. Schäfer, J. Schaefer, V. Schemann, I. Schirmacher, J. Schmidt, S. Schmidt, J. Schneider, S. Schnitt, A. Schwarz, H. Siebert, H. Sodemann, T. Sperzel, G. Spreen, B. Stevens, F. Stratmann, G. Svensson, C. Tatzelt, T. Tuch, T. Vihma, C. Voigt, L. Volkmer, A. Walbröl, A. Weber, B. Wehner, B. Wetzel, M. Wirth, T. Zinner
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 8865-8892 (2024)
Global warming is amplified in the Arctic. However, numerical models struggle to represent key processes that determine Arctic weather and climate. To collect data that help to constrain the models, the HALO–(𝒜𝒞)3 aircraft campaign was conduc
Externí odkaz:
https://doaj.org/article/bca9d009d9254c2ea20e8a7af06088e2
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 8771-8795 (2024)
This study emulates dropsondes to elucidate the extent to which sporadic airborne sondes adequately represent divergence of moisture transport in Arctic atmospheric rivers (ARs). The convergence of vertically integrated moisture transport (IVT) plays
Externí odkaz:
https://doaj.org/article/ca141fa97e444766ae07f5fdabeedab3