Zobrazeno 1 - 10
of 182
pro vyhledávání: '"Newman, Dava"'
Publikováno v:
Bulletin of the American Academy of Arts and Sciences, 2024 Jan 01. 77(2), 46-53.
Externí odkaz:
https://www.jstor.org/stable/27285405
Autor:
Lacoste, Alexandre, Lehmann, Nils, Rodriguez, Pau, Sherwin, Evan David, Kerner, Hannah, Lütjens, Björn, Irvin, Jeremy Andrew, Dao, David, Alemohammad, Hamed, Drouin, Alexandre, Gunturkun, Mehmet, Huang, Gabriel, Vazquez, David, Newman, Dava, Bengio, Yoshua, Ermon, Stefano, Zhu, Xiao Xiang
Recent progress in self-supervision has shown that pre-training large neural networks on vast amounts of unsupervised data can lead to substantial increases in generalization to downstream tasks. Such models, recently coined foundation models, have b
Externí odkaz:
http://arxiv.org/abs/2306.03831
Numerical simulations in climate, chemistry, or astrophysics are computationally too expensive for uncertainty quantification or parameter-exploration at high-resolution. Reduced-order or surrogate models are multiple orders of magnitude faster, but
Externí odkaz:
http://arxiv.org/abs/2207.11417
When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI
Generative AI techniques like those that synthesize images from text (text-to-image models) offer new possibilities for creatively imagining new ideas. We investigate the capabilities of these models to help communities engage in conversations about
Externí odkaz:
http://arxiv.org/abs/2206.00533
Autor:
Jiang, Peishi, Meinert, Nis, Jordão, Helga, Weisser, Constantin, Holgate, Simon, Lavin, Alexander, Lütjens, Björn, Newman, Dava, Wainwright, Haruko, Walker, Catherine, Barnard, Patrick
Developing fast and accurate surrogates for physics-based coastal and ocean models is an urgent need due to the coastal flood risk under accelerating sea level rise, and the computational expense of deterministic numerical models. For this purpose, w
Externí odkaz:
http://arxiv.org/abs/2110.07100
The transition to green energy grids depends on detailed wind and solar forecasts to optimize the siting and scheduling of renewable energy generation. Operational forecasts from numerical weather prediction models, however, only have a spatial resol
Externí odkaz:
http://arxiv.org/abs/2109.08770
Climate models project an uncertainty range of possible warming scenarios from 1.5 to 5 degree Celsius global temperature increase until 2100, according to the CMIP6 model ensemble. Climate risk management and infrastructure adaptation requires the a
Externí odkaz:
http://arxiv.org/abs/2105.02939
Autor:
Lütjens, Björn, Leshchinskiy, Brandon, Boulais, Océane, Chishtie, Farrukh, Díaz-Rodríguez, Natalia, Masson-Forsythe, Margaux, Mata-Payerro, Ana, Requena-Mesa, Christian, Sankaranarayanan, Aruna, Piña, Aaron, Gal, Yarin, Raïssi, Chedy, Lavin, Alexander, Newman, Dava
Deep generative vision models are now able to synthesize realistic-looking satellite imagery. But, the possibility of hallucinations prevents their adoption for risk-sensitive applications, such as generating materials for communicating climate chang
Externí odkaz:
http://arxiv.org/abs/2104.04785
Autor:
Lavin, Alexander, Gilligan-Lee, Ciarán M., Visnjic, Alessya, Ganju, Siddha, Newman, Dava, Baydin, Atılım Güneş, Ganguly, Sujoy, Lange, Danny, Sharma, Amit, Zheng, Stephan, Xing, Eric P., Gibson, Adam, Parr, James, Mattmann, Chris, Gal, Yarin
The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives
Externí odkaz:
http://arxiv.org/abs/2101.03989
Autor:
Lütjens, Björn, Leshchinskiy, Brandon, Requena-Mesa, Christian, Chishtie, Farrukh, Díaz-Rodriguez, Natalia, Boulais, Océane, Piña, Aaron, Newman, Dava, Lavin, Alexander, Gal, Yarin, Raïssi, Chedy
As climate change increases the intensity of natural disasters, society needs better tools for adaptation. Floods, for example, are the most frequent natural disaster, but during hurricanes the area is largely covered by clouds and emergency managers
Externí odkaz:
http://arxiv.org/abs/2010.08103