8.9k citations · 11.5k across the 56 of their papers we have counts for
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Contrastive Topographic Models: Energy-based density models applied to the understanding of sensory coding and cortical topography
Simon Osindero
We address the problem of building theoretical models that help elucidate the function of the visual brain at computational/algorithmic and structural/mechanistic levels. We seek t…
From Language Games to Drawing Games
Chrisantha Fernando, Daria Zenkova, Stanislav Nikolov +1
We attempt to automate various artistic processes by inventing a set of drawing games, analogous to the approach taken by emergent language research in inventing communication game…
Small Data, Big Decisions: Model Selection in the Small-Data Regime
Jorg Bornschein, Francesco Visin, Simon Osindero
Highly overparametrized neural networks can display curiously strong generalization performance - a phenomenon that has recently garnered a wealth of theoretical and empirical rese…
AlgebraNets
Jordan Hoffmann, Simon Schmitt, Simon Osindero +2
Neural networks have historically been built layerwise from the set of functions in , i.e. with activations and weights/parameters represented…
A Practical Sparse Approximation for Real Time Recurrent Learning
Jacob Menick, Erich Elsen, Utku Evci +3
Current methods for training recurrent neural networks are based on backpropagation through time, which requires storing a complete history of network states, and prohibits updatin…
A Deep Neural Network's Loss Surface Contains Every Low-dimensional Pattern
Wojciech Marian Czarnecki, Simon Osindero, Razvan Pascanu +1
The work "Loss Landscape Sightseeing with Multi-Point Optimization" (Skorokhodov and Burtsev, 2019) demonstrated that one can empirically find arbitrary 2D binary patterns inside l…