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pro vyhledávání: '"Liška, Adam"'
Autor:
Liska, Adam
Functional Magnetic Resonance Imaging (fMRI) has consistently highlighted aberrant functional connectivity across brain regions of autism spectrum disorder (ASD) patients. However, the manifestation and neural substrates of these alterations are high
Externí odkaz:
https://hdl.handle.net/11572/369283
Autor:
Liška, Adam, Kočiský, Tomáš, Gribovskaya, Elena, Terzi, Tayfun, Sezener, Eren, Agrawal, Devang, d'Autume, Cyprien de Masson, Scholtes, Tim, Zaheer, Manzil, Young, Susannah, Gilsenan-McMahon, Ellen, Austin, Sophia, Blunsom, Phil, Lazaridou, Angeliki
Knowledge and language understanding of models evaluated through question answering (QA) has been usually studied on static snapshots of knowledge, like Wikipedia. However, our world is dynamic, evolves over time, and our models' knowledge becomes ou
Externí odkaz:
http://arxiv.org/abs/2205.11388
Autor:
Lazaridou, Angeliki, Kuncoro, Adhiguna, Gribovskaya, Elena, Agrawal, Devang, Liska, Adam, Terzi, Tayfun, Gimenez, Mai, d'Autume, Cyprien de Masson, Kocisky, Tomas, Ruder, Sebastian, Yogatama, Dani, Cao, Kris, Young, Susannah, Blunsom, Phil
Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contrasts with the current static language modelling paradigm, which trains
Externí odkaz:
http://arxiv.org/abs/2102.01951
Neural networks are very powerful learning systems, but they do not readily generalize from one task to the other. This is partly due to the fact that they do not learn in a compositional way, that is, by discovering skills that are shared by differe
Externí odkaz:
http://arxiv.org/abs/1802.06467
The goal of the present study is to identify autism using machine learning techniques and resting-state brain imaging data, leveraging the temporal variability of the functional connections (FC) as the only information. We estimated and compared the
Externí odkaz:
http://arxiv.org/abs/1712.08041
Akademický článek
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Autor:
Whitesell, Jennifer D., Liska, Adam, Coletta, Ludovico, Hirokawa, Karla E., Bohn, Phillip, Williford, Ali, Groblewski, Peter A., Graddis, Nile, Kuan, Leonard, Knox, Joseph E., Ho, Anh, Wakeman, Wayne, Nicovich, Philip R., Nguyen, Thuc Nghi, van Velthoven, Cindy T.J., Garren, Emma, Fong, Olivia, Naeemi, Maitham, Henry, Alex M., Dee, Nick, Smith, Kimberly A., Levi, Boaz, Feng, David, Ng, Lydia, Tasic, Bosiljka, Zeng, Hongkui, Mihalas, Stefan, Gozzi, Alessandro, Harris, Julie A.
Publikováno v:
In Neuron 3 February 2021 109(3):545-559
As automated image analysis progresses, there is increasing interest in richer linguistic annotation of pictures, with attributes of objects (e.g., furry, brown...) attracting most attention. By building on the recent "zero-shot learning" approach, a
Externí odkaz:
http://arxiv.org/abs/1501.02714
Publikováno v:
In NeuroImage 15 July 2015 115:281-291
Publikováno v:
In Journal of Cleaner Production 15 July 2014 75:31-39