Demixing odors - fast inference in olfaction. - Agnieszka Grabska-Barwinska; Jeffrey M. Beck; Alexandre Pouget; Peter E. Latham (NIPS, 2013)

Optimal prior-dependent neural population codes under shared input noise. - Agnieszka Grabska-Barwinska; Jonathan W. Pillow (NIPS, 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)

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; et al. (CoRR, 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; et al. (Nat., 2016)

Online Learning with Gated Linear Networks. - Joel Veness; Tor Lattimore; Avishkar Bhoopchand; Agnieszka Grabska-Barwinska; Christopher Mattern; Peter Toth (CoRR, 2017)

Progress & Compress: A scalable framework for continual learning. - Jonathan Schwarz; Wojciech Czarnecki 001; Jelena Luketina; Agnieszka Grabska-Barwinska; Yee Whye Teh; Razvan Pascanu; Raia Hadsell (ICML, 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; et al. (CoRR, 2018)

Gated Linear Networks. - Joel Veness; Tor Lattimore; Avishkar Bhoopchand; David Budden; Christopher Mattern; Agnieszka Grabska-Barwinska; Peter Toth; Simon Schmitt; Marcus Hutter (CoRR, 2019)

Measuring and improving the quality of visual explanations. - Agnieszka Grabska-Barwinska (CoRR, 2020)

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 (AAAI, 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; et al. (CoRR, 2021)