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2020 – today
- 2021
[c4]Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter:
Gated Linear Networks. AAAI 2021: 10015-10023- [i7]Skanda Koppula, Victor Bapst, Marc Huertas-Company
, Sam Blackwell, Agnieszka Grabska-Barwinska, Sander Dieleman, Andrea Huber, Natasha Antropova, Mikolaj Binkowski, Hannah Openshaw, Adrià Recasens, Fernando Caro, Avishai Deke, Yohan Dubois, Jesus Vega Ferrero, David C. Koo, Joel R. Primack, Trevor Back:
A Deep Learning Approach for Characterizing Major Galaxy Mergers. CoRR abs/2102.05182 (2021) - 2020
- [i6]Agnieszka Grabska-Barwinska:
Measuring and improving the quality of visual explanations. CoRR abs/2003.08774 (2020)
2010 – 2019
- 2019
- [i5]Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter:
Gated Linear Networks. CoRR abs/1910.01526 (2019) - 2018
- [c3]Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell:
Progress & Compress: A scalable framework for continual learning. ICML 2018: 4535-4544 - [i4]Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack W. Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harley, Josh Abramson, Shakir Mohamed, Danilo Jimenez Rezende, David Saxton, Adam Cain, Chloe Hillier, David Silver, Koray Kavukcuoglu, Matthew M. Botvinick, Demis Hassabis, Timothy P. Lillicrap:
Unsupervised Predictive Memory in a Goal-Directed Agent. CoRR abs/1803.10760 (2018) - [i3]Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell:
Progress & Compress: A scalable framework for continual learning. CoRR abs/1805.06370 (2018) - 2017
- [i2]Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth:
Online Learning with Gated Linear Networks. CoRR abs/1712.01897 (2017) - 2016
- [j2]Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John P. Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis:
Hybrid computing using a neural network with dynamic external memory. Nat. 538(7626): 471-476 (2016) - [i1]James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell:
Overcoming catastrophic forgetting in neural networks. CoRR abs/1612.00796 (2016) - 2014
- [j1]Agnieszka Grabska-Barwinska, Peter E. Latham:
How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes? J. Comput. Neurosci. 36(3): 469-481 (2014) - [c2]Agnieszka Grabska-Barwinska, Jonathan W. Pillow:
Optimal prior-dependent neural population codes under shared input noise. NIPS 2014: 1880-1888 - 2013
- [c1]Agnieszka Grabska-Barwinska, Jeffrey M. Beck, Alexandre Pouget, Peter E. Latham:
Demixing odors - fast inference in olfaction. NIPS 2013: 1968-1976
Coauthor Index
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