Zobrazeno 1 - 9
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pro vyhledávání: '"Bornschein, Jörg"'
Autor:
Fisch, Adam, Rannen-Triki, Amal, Pascanu, Razvan, Bornschein, Jörg, Lazaridou, Angeliki, Gribovskaya, Elena, Ranzato, Marc'Aurelio
As the application space of language models continues to evolve, a natural question to ask is how we can quickly adapt models to new tasks. We approach this classic question from a continual learning perspective, in which we aim to continue fine-tuni
Externí odkaz:
http://arxiv.org/abs/2307.05741
Autor:
Zaidi, Sheheryar, Berariu, Tudor, Kim, Hyunjik, Bornschein, Jörg, Clopath, Claudia, Teh, Yee Whye, Pascanu, Razvan
Re-initializing a neural network during training has been observed to improve generalization in recent works. Yet it is neither widely adopted in deep learning practice nor is it often used in state-of-the-art training protocols. This raises the ques
Externí odkaz:
http://arxiv.org/abs/2206.10011
Autor:
Exarchakis, Georgios, Bornschein, Jörg, Sheikh, Abdul-Saboor, Dai, Zhenwen, Henniges, Marc, Drefs, Jakob, Lücke, Jörg
ProSper is a python library containing probabilistic algorithms to learn dictionaries. Given a set of data points, the implemented algorithms seek to learn the elementary components that have generated the data. The library widens the scope of dictio
Externí odkaz:
http://arxiv.org/abs/1908.06843
Aiming to augment generative models with external memory, we interpret the output of a memory module with stochastic addressing as a conditional mixture distribution, where a read operation corresponds to sampling a discrete memory address and retrie
Externí odkaz:
http://arxiv.org/abs/1709.07116
Autor:
Bornschein, Jörg, Bengio, Yoshua
Training deep directed graphical models with many hidden variables and performing inference remains a major challenge. Helmholtz machines and deep belief networks are such models, and the wake-sleep algorithm has been proposed to train them. The wake
Externí odkaz:
http://arxiv.org/abs/1406.2751
Akademický článek
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Publikováno v:
PLoS Computational Biology. Jun2013, Vol. 9 Issue 6, p1-16. 16p. 1 Illustration.
Akademický článek
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Publikováno v:
Latent Variable Analysis & Signal Separation; 2010, p450-457, 8p