Zobrazeno 1 - 10
of 39 397
pro vyhledávání: '"Emulators"'
Reliability analysis is a sub-field of uncertainty quantification that assesses the probability of a system performing as intended under various uncertainties. Traditionally, this analysis relies on deterministic models, where experiments are repeata
Externí odkaz:
http://arxiv.org/abs/2412.13731
Autor:
Eftekhari, Aryan, Folini, Doris, Friedl, Aleksandra, Kübler, Felix, Scheidegger, Simon, Schenk, Olaf
This paper presents a framework for developing efficient and interpretable carbon-cycle emulators (CCEs) as part of climate emulators in Integrated Assessment Models, enabling economists to custom-build CCEs accurately calibrated to advanced climate
Externí odkaz:
http://arxiv.org/abs/2411.10768
We introduce the Autoregressive PDE Emulator Benchmark (APEBench), a comprehensive benchmark suite to evaluate autoregressive neural emulators for solving partial differential equations. APEBench is based on JAX and provides a seamlessly integrated d
Externí odkaz:
http://arxiv.org/abs/2411.00180
We employ a novel framework for accelerated cosmological inference, based on neural emulators and gradient-based sampling methods, to forecast constraints on dark energy models from Stage IV cosmic shear surveys. We focus on dark scattering (DS), an
Externí odkaz:
http://arxiv.org/abs/2410.10603
Autor:
Viti, Bruno, Thaler, Franz, Kapper, Kathrin Lisa, Urschler, Martin, Holler, Martin, Karabelas, Elias
Segmentation of cardiac magnetic resonance images (MRI) is crucial for the analysis and assessment of cardiac function, helping to diagnose and treat various cardiovascular diseases. Most recent techniques rely on deep learning and usually require an
Externí odkaz:
http://arxiv.org/abs/2411.06911
Autor:
Teng, Elizabeth, Demir, Ugur, Doctor, Zoheyr, Srivastava, Philipp M., Lalvani, Shamal, Kalogera, Vicky, Katsaggelos, Aggelos, Andrews, Jeff J., Bavera, Simone S., Briel, Max M., Gossage, Seth, Kovlakas, Konstantinos, Kruckow, Matthias U., Rocha, Kyle Akira, Sun, Meng, Xing, Zepei, Zapartas, Emmanouil
Knowledge about the internal physical structure of stars is crucial to understanding their evolution. The novel binary population synthesis code POSYDON includes a module for interpolating the stellar and binary properties of any system at the end of
Externí odkaz:
http://arxiv.org/abs/2410.11105
Full-complexity Earth system models (ESMs) are computationally very expensive, limiting their use in exploring the climate outcomes of multiple emission pathways. More efficient emulators that approximate ESMs can directly map emissions onto climate
Externí odkaz:
http://arxiv.org/abs/2408.05288
Autor:
Wesselkamp, Marieke, Chantry, Matthew, Pinnington, Ewan, Choulga, Margarita, Boussetta, Souhail, Kalweit, Maria, Boedecker, Joschka, Dormann, Carsten F., Pappenberger, Florian, Balsamo, Gianpaolo
Most useful weather prediction for the public is near the surface. The processes that are most relevant for near-surface weather prediction are also those that are most interactive and exhibit positive feedback or have key role in energy partitioning
Externí odkaz:
http://arxiv.org/abs/2407.16463
Autor:
Abdulah, Sameh, Baker, Allison H., Bosilca, George, Cao, Qinglei, Castruccio, Stefano, Genton, Marc G., Keyes, David E., Khalid, Zubair, Ltaief, Hatem, Song, Yan, Stenchikov, Georgiy L., Sun, Ying
We present the design and scalable implementation of an exascale climate emulator for addressing the escalating computational and storage requirements of high-resolution Earth System Model simulations. We utilize the spherical harmonic transform to s
Externí odkaz:
http://arxiv.org/abs/2408.04440
Autor:
Yik, William, Silva, Sam J.
Neural network emulators have become an invaluable tool for a wide variety of climate and weather prediction tasks. While showing incredibly promising results, these networks do not have an inherent ability to produce equitable predictions. That is,
Externí odkaz:
http://arxiv.org/abs/2406.19636