Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Yuki M. Asano"'
Autor:
Lukas Kondmann, Caglar Senaras, Yuki M. Asano, Akhil Singh Rana, Annett Wania, Xiao Xiang Zhu
Increasing coverage of commercial and public satellites allows us to monitor the pulse of the Earth in ever-shorter frequency (Zhu et al., 2017). Together with the rise of deep learning in artificial intelligence (AI) (LeCun et al., 2015), the field
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78fa70a46069300321b9be2422a5b7dc
https://doi.org/10.5194/egusphere-egu23-2843
https://doi.org/10.5194/egusphere-egu23-2843
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198328
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68153e6807efdda4b0ac24170047f8e9
https://doi.org/10.1007/978-3-031-19833-5_43
https://doi.org/10.1007/978-3-031-19833-5_43
Autor:
Conrad Borchers, Dalia Gala, Benjamin Gilburt, Eduard Oravkin, Wilfried Bounsi, Yuki M Asano, Hannah Kirk
The growing capability and availability of generative language models has enabled a wide range of new downstream tasks. Academic research has identified, quantified and mitigated biases present in language models but is rarely tailored to downstream
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3fb0a7e65efba377a1c07b03ea9a4923
http://arxiv.org/abs/2205.11374
http://arxiv.org/abs/2205.11374
Autor:
Adrian Ziegler, Yuki M. Asano
Progress in self-supervised learning has brought strong general image representation learning methods. Yet so far, it has mostly focused on image-level learning. In turn, tasks such as unsupervised image segmentation have not benefited from this tren
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67a715e04f9d8a03472cdee805518fb6
Autor:
Yuki M. Asano, Gesa Biermann
Publikováno v:
Nature Sustainability. 2:621-627
The current and growing demand for animal protein exerts immense pressure on the environment through diverse effects such as land-use change, water use and greenhouse gas emissions. Curbing meat demand by transitioning to largely plant-based diets is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d527f5b4bb86c1dd962825bacdbb46c8
https://doi.org/10.1038/s41893-019-0316-0
https://doi.org/10.1038/s41893-019-0316-0
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Proceedings of the National Academy of Sciences of the United States of America, 118(27):e2025721118. National Academy of Sciences
Proceedings of the National Academy of Sciences of the United States of America, 118(27):e2025721118. National Academy of Sciences
Significance Macroeconomic models play an important role in guiding fiscal and monetary policy. At the core of many of these models is the assumption of a single representative, rational agent. We develop a model that loosens these constraints and ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a2d5074258966c2c86bf5558c5ba4f9
https://pubmed.ncbi.nlm.nih.gov/34215696
https://pubmed.ncbi.nlm.nih.gov/34215696
Autor:
Aleksandar Shtedritski, Paulius Rauba, Noah Broestl, Hannah Rose Kirk, Xingjian Bai, Martin Doff-Sotta, Gal Wachtel, Yuki M. Asano, Yennie Jun, Ruining Li
Publikováno v:
Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021).
Hateful memes pose a unique challenge for current machine learning systems because their message is derived from both text- and visual-modalities. To this effect, Facebook released the Hateful Memes Challenge, a dataset of memes with pre-extracted te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39ce189d1c87ee225f6d78945eb84506
https://doi.org/10.18653/v1/2021.woah-1.4
https://doi.org/10.18653/v1/2021.woah-1.4
Autor:
Mandela Patrick, Yuki M. Asano, Polina Kuznetsova, Ruth Fong, Joao F. Henriques, Geoffrey Zweig, Andrea Vedaldi
In the image domain, excellent representations can be learned by inducing invariance to content-preserving transformations via noise contrastive learning. In this paper, we generalize contrastive learning to a wider set of transformations, and their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ac6dd624d953b5229211a2cbf5eba4e
Publikováno v:
SSRN Electronic Journal.
Standard macroeconomic models assume that households are rational in the sense that they are perfect utility maximizers, and explain economic dynamics in terms of shocks that drive the economy away from the steady-state. Here we build on a standard m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5e0b65da27844bba04ef73184f32d98
https://doi.org/10.2139/ssrn.3415472
https://doi.org/10.2139/ssrn.3415472
Autor:
N Arbor, Etienne Testa, Katia Parodi, Georgios Dedes, Simon Rit, Denis Dauvergne, Jean Michel Létang, Yuki M. Asano
Publikováno v:
Medical Physics. 42:3298-3298
Purpose: The quantification of the intrinsic performances of proton computed tomography (pCT) as a modality for treatment planning in proton therapy. The performance of an ideal pCT scanner is studied as a function of various parameters. Methods: Usi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d1a143e33d64157f5f3eeab2f5681c9
https://doi.org/10.1118/1.4924232
https://doi.org/10.1118/1.4924232