Agnieszka Grabska-Barwinska

According to our database, Agnieszka Grabska-Barwinska authored at least 12 papers between 2013 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2021

A Deep Learning Approach for Characterizing Major Galaxy Mergers.

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

CoRR, 2021

Gated Linear Networks.

Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Measuring and improving the quality of visual explanations.

Agnieszka Grabska-Barwinska

CoRR, 2020

2019

Gated Linear Networks.

Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter

CoRR, 2019

2018

Unsupervised Predictive Memory in a Goal-Directed Agent.

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

CoRR, 2018

Progress & Compress: A scalable framework for continual learning.

Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Online Learning with Gated Linear Networks.

Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth

CoRR, 2017

2016

Hybrid computing using a neural network with dynamic external memory.

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

Nat., 2016

Overcoming catastrophic forgetting in neural networks.

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

CoRR, 2016

2014

How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

Agnieszka Grabska-Barwinska, Peter E. Latham

J. Comput. Neurosci., 2014

Optimal prior-dependent neural population codes under shared input noise.

Agnieszka Grabska-Barwinska, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Demixing odors - fast inference in olfaction.

Agnieszka Grabska-Barwinska, Jeffrey M. Beck, Alexandre Pouget, Peter E. Latham

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013