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

31 October 2018

Jakob H. Macke

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

34 / 34 papers shown

Title
Emergent representations in networks trained with the Forward-Forward algorithm Niccolo Tosato Lorenzo Basile Emanuele Ballarin Giuseppe de Alteriis Alberto Cazzaniga A. Ansuini 46 9 0 26 May 2023
Untangling in Invariant Speech Recognition Cory Stephenson J. Feather Suchismita Padhy Oguz H. Elibol Hanlin Tang Josh H. McDermott SueYeon Chung SSL 57 31 0 03 Mar 2020
Generalisation in humans and deep neural networks Robert Geirhos Carlos R. Medina Temme Jonas Rauber Heiko H. Schutt Matthias Bethge Felix Wichmann OOD 107 606 0 27 Aug 2018
Diverse feature visualizations reveal invariances in early layers of deep neural networks Santiago A. Cadena Marissa A. Weis Leon A. Gatys Matthias Bethge Alexander S. Ecker FAtt 38 28 0 27 Jul 2018
Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos M. Raghu Samy Bengio DRL 58 446 0 14 Jun 2018
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 82 117 0 07 Jun 2018
Measuring the Intrinsic Dimension of Objective Landscapes Chunyuan Li Heerad Farkhoor Rosanne Liu J. Yosinski 78 410 0 24 Apr 2018
Emergence of grid-like representations by training recurrent neural networks to perform spatial localization Christopher J. Cueva Xue-Xin Wei 43 216 0 21 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 64 333 0 19 Mar 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 65 1,345 0 12 Dec 2017
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 160 245 0 06 Nov 2017
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations M. Nonnenmacher Srinivas C. Turaga Jakob H. Macke 43 21 0 06 Nov 2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders Artur Speiser Jinyao Yan Evan Archer Lars Buesing Srinivas C. Turaga Jakob H. Macke BDL 52 47 0 06 Nov 2017
Classification and Geometry of General Perceptual Manifolds SueYeon Chung Daniel D. Lee H. Sompolinsky 52 154 0 17 Oct 2017
Emergence of Invariance and Disentanglement in Deep Representations Alessandro Achille Stefano Soatto OOD DRL 88 476 0 05 Jun 2017
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 110 772 0 15 Mar 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks Wenjie Luo Yujia Li R. Urtasun R. Zemel HAI 87 1,796 0 15 Jan 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 332 4,624 0 10 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhiwen Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 891 6,787 0 26 Sep 2016
The Latin American Giant Observatory: a successful collaboration in Latin America based on Cosmic Rays and computer science domains Hernán Asorey R. Mayo-García L. Núñez M. Pascual A. J. Rubio-Montero M. Suárez-Durán L. A. Torres-Niño 81 5 0 30 May 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 57 155 0 26 May 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 156 158 0 20 May 2016
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images Aravindh Mahendran Andrea Vedaldi FAtt 68 534 0 07 Dec 2015
Convergent Learning: Do different neural networks learn the same representations? Yixuan Li J. Yosinski Jeff Clune Hod Lipson John E. Hopcroft SSL 81 368 0 24 Nov 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 122 1,871 0 22 Jun 2015
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 185 1,582 0 09 Mar 2015
Understanding Deep Image Representations by Inverting Them Aravindh Mahendran Andrea Vedaldi FAtt 107 1,963 0 26 Nov 2014
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parameters D. Kobak Wieland Brendel C. Constantinidis C. Feierstein Adam Kepecs Z. Mainen R. Romo Xue-Lian Qi N. Uchida C. Machens 79 466 0 22 Oct 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,330 0 04 Sep 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 437 16,940 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 585 15,874 0 12 Nov 2013
Predicting Parameters in Deep Learning Misha Denil B. Shakibi Laurent Dinh MarcÁurelio Ranzato Nando de Freitas OOD 192 1,317 0 03 Jun 2013
Building high-level features using large scale unsupervised learning Quoc V. Le MarcÁurelio Ranzato R. Monga M. Devin Kai Chen G. Corrado J. Dean A. Ng SSL OffRL CVBM 116 2,269 0 29 Dec 2011
Online Identification and Tracking of Subspaces from Highly Incomplete Information Laura Balzano Robert D. Nowak Benjamin Recht 112 424 0 21 Jun 2010