Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Schneider, Rosalia"'
Autor:
Zambaldi, Vinicius, La, David, Chu, Alexander E., Patani, Harshnira, Danson, Amy E., Kwan, Tristan O. C., Frerix, Thomas, Schneider, Rosalia G., Saxton, David, Thillaisundaram, Ashok, Wu, Zachary, Moraes, Isabel, Lange, Oskar, Papa, Eliseo, Stanton, Gabriella, Martin, Victor, Singh, Sukhdeep, Wong, Lai H., Bates, Russ, Kohl, Simon A., Abramson, Josh, Senior, Andrew W., Alguel, Yilmaz, Wu, Mary Y., Aspalter, Irene M., Bentley, Katie, Bauer, David L. V., Cherepanov, Peter, Hassabis, Demis, Kohli, Pushmeet, Fergus, Rob, Wang, Jue
Computational design of protein-binding proteins is a fundamental capability with broad utility in biomedical research and biotechnology. Recent methods have made strides against some target proteins, but on-demand creation of high-affinity binders w
Externí odkaz:
http://arxiv.org/abs/2409.08022
Autor:
Moreno, Pol, Kosiorek, Adam R., Strathmann, Heiko, Zoran, Daniel, Schneider, Rosalia G., Winckler, Björn, Markeeva, Larisa, Weber, Théophane, Rezende, Danilo J.
NeRF provides unparalleled fidelity of novel view synthesis: rendering a 3D scene from an arbitrary viewpoint. NeRF requires training on a large number of views that fully cover a scene, which limits its applicability. While these issues can be addre
Externí odkaz:
http://arxiv.org/abs/2301.05747
Autor:
Kosiorek, Adam R., Strathmann, Heiko, Zoran, Daniel, Moreno, Pol, Schneider, Rosalia, Mokrá, Soňa, Rezende, Danilo J.
We propose NeRF-VAE, a 3D scene generative model that incorporates geometric structure via NeRF and differentiable volume rendering. In contrast to NeRF, our model takes into account shared structure across scenes, and is able to infer the structure
Externí odkaz:
http://arxiv.org/abs/2104.00587
Autor:
Hendricks, Lisa Anne, Mellor, John, Schneider, Rosalia, Alayrac, Jean-Baptiste, Nematzadeh, Aida
Recently multimodal transformer models have gained popularity because their performance on language and vision tasks suggest they learn rich visual-linguistic representations. Focusing on zero-shot image retrieval tasks, we study three important fact
Externí odkaz:
http://arxiv.org/abs/2102.00529
Autor:
Alayrac, Jean-Baptiste, Recasens, Adrià, Schneider, Rosalia, Arandjelović, Relja, Ramapuram, Jason, De Fauw, Jeffrey, Smaira, Lucas, Dieleman, Sander, Zisserman, Andrew
Videos are a rich source of multi-modal supervision. In this work, we learn representations using self-supervision by leveraging three modalities naturally present in videos: visual, audio and language streams. To this end, we introduce the notion of
Externí odkaz:
http://arxiv.org/abs/2006.16228
Autor:
Das, Abhishek, Carnevale, Federico, Merzic, Hamza, Rimell, Laura, Schneider, Rosalia, Abramson, Josh, Hung, Alden, Ahuja, Arun, Clark, Stephen, Wayne, Gregory, Hill, Felix
Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose question-answering as a general paradigm to decode and understand the represe
Externí odkaz:
http://arxiv.org/abs/2006.01016
Autor:
Hill, Felix, Lampinen, Andrew, Schneider, Rosalia, Clark, Stephen, Botvinick, Matthew, McClelland, James L., Santoro, Adam
The question of whether deep neural networks are good at generalising beyond their immediate training experience is of critical importance for learning-based approaches to AI. Here, we consider tests of out-of-sample generalisation that require an ag
Externí odkaz:
http://arxiv.org/abs/1910.00571
Akademický článek
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Akademický článek
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Autor:
Jun Cheng, Novati, Guido, Pan, Joshua, Bycroft, Clare, Žemgulyte, Akvile, Applebaum, Taylor, Pritzel, Alexander, Lai Hong Wong, Zielinski, Michal, Sargeant, Tobias, Schneider, Rosalia G., Senior, Andrew W., Jumper, John, Hassabis, Demis, Kohli, Pushmeet, Avsec, Žiga
Publikováno v:
Science; 9/22/2023, Vol. 381 Issue 6664, p1303-1303, 1p, 1 Diagram
