p7q-bio.NC

q-bio.NC

37 papers

Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli

1503.03585

A Neural Algorithm of Artistic Style

Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

1508.06576

Towards deep learning with segregated dendrites

Jordan Guergiuev, Timothy P. Lillicrap, Blake A. Richards

1610.00161

Unsupervised Learning of Visual Structure using Predictive Generative Networks

William Lotter, Gabriel Kreiman, David Cox

1511.06380

High-dimensional dynamics of generalization error in neural networks

Madhu S. Advani, Andrew M. Saxe

1710.03667

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, Wieland Brendel

1811.12231

Shortcut Learning in Deep Neural Networks

Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, Felix A. Wichmann

2004.07780

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny

2103.03230

Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Andrew M. Saxe, James L. McClelland, Surya Ganguli

1312.6120

Early Visual Concept Learning with Unsupervised Deep Learning

Irina Higgins, Loic Matthey, Xavier Glorot, Arka Pal, Benigno Uria, Charles Blundell, Shakir Mohamed, Alexander Lerchner

1606.05579

A mathematical theory of semantic development in deep neural networks

Andrew M. Saxe, James L. McClelland, Surya Ganguli

1810.10531

Similarity of Neural Network Representations Revisited

Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey Hinton

1905.00414

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

William Lotter, Gabriel Kreiman, David Cox

1605.08104

Linear dynamical neural population models through nonlinear embeddings

Yuanjun Gao, Evan Archer, Liam Paninski, John P. Cunningham

1605.08454

Continual Learning Through Synaptic Intelligence

Friedemann Zenke, Ben Poole, Surya Ganguli

1703.04200

On the surprising similarities between supervised and self-supervised models

Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Matthias Bethge, Felix A. Wichmann, Wieland Brendel

2010.08377

Emergence of grid-like representations by training recurrent neural networks to perform spatial localization

Christopher J. Cueva, Xue-Xin Wei

1803.07770

Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency

Robert Geirhos, Kristof Meding, Felix A. Wichmann

2006.16736

Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics

Daniel Kunin, Javier Sagastuy-Brena, Surya Ganguli, Daniel L. K. Yamins, Hidenori Tanaka

2012.04728

Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains

Samira Abnar, Lisa Beinborn, Rochelle Choenni, Willem Zuidema

1906.01539

Trivial or impossible -- dichotomous data difficulty masks model differences (on ImageNet and beyond)

Kristof Meding, Luca M. Schulze Buschoff, Robert Geirhos, Felix A. Wichmann

2110.05922

Random feedback weights support learning in deep neural networks

Timothy P. Lillicrap, Daniel Cownden, Douglas B. Tweed, Colin J. Akerman

1411.0247

Linking artificial and human neural representations of language

Jon Gauthier, Roger Levy

1910.01244

Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains

Yuan Zhao, Il Memming Park

1604.03053

Deep neuroethology of a virtual rodent

Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa, Greg Wayne, Bence Ölveczky

1911.09451

Biologically inspired protection of deep networks from adversarial attacks

Aran Nayebi, Surya Ganguli

1703.09202

Analyzing biological and artificial neural networks: challenges with opportunities for synergy?

David G. T. Barrett, Ari S. Morcos, Jakob H. Macke

1810.13373

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Brain's Ventral Visual Pathway

Umut Güçlü, Marcel A. J. van Gerven

1411.6422

Mind Reader: Reconstructing complex images from brain activities

Sikun Lin, Thomas Sprague, Ambuj K Singh

2210.01769

What can topology tell us about the neural code?

Carina Curto

1605.01905

Markerless tracking of user-defined features with deep learning

Alexander Mathis, Pranav Mamidanna, Taiga Abe, Kevin M. Cury, Venkatesh N. Murthy, Mackenzie W. Mathis, Matthias Bethge

1804.03142

A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks

Owen Marschall, Kyunghyun Cho, Cristina Savin

1907.02649

Model-Free Episodic Control

Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z Leibo, Jack Rae, Daan Wierstra, Demis Hassabis

1606.04460

Continual Lifelong Learning with Neural Networks: A Review

German I. Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan, Stefan Wermter

1802.07569

Clique topology reveals intrinsic geometric structure in neural correlations

Chad Giusti, Eva Pastalkova, Carina Curto, Vladimir Itskov

1502.06172

Two's company, three (or more) is a simplex: Algebraic-topological tools for understanding higher-order structure in neural data

Chad Giusti, Robert Ghrist, Danielle S. Bassett

1601.01704

Generalisation in humans and deep neural networks

Robert Geirhos, Carlos R. Medina Temme, Jonas Rauber, Heiko H. Schütt, Matthias Bethge, Felix A. Wichmann

1808.08750