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Insights on representational similarity in neural networks with canonical correlation

14 June 2018

Papers citing "Insights on representational similarity in neural networks with canonical correlation"

22 / 22 papers shown

Title
Exploring Causes of Representational Similarity in Machine Learning Models Zeyu Michael Li Hung Anh Vu Damilola Awofisayo Emily Wenger CML 252 0 0 20 May 2025
ReSi: A Comprehensive Benchmark for Representational Similarity Measures Max Klabunde Tassilo Wald Tobias Schumacher Klaus H. Maier-Hein Markus Strohmaier Adriana Iamnitchi AI4TS VLM 225 6 0 13 Mar 2025
Mapping fMRI Signal and Image Stimuli in an Artificial Neural Network Latent Space: Bringing Artificial and Natural Minds Together Cesare Maria Dalbagno Manuel de Castro Ribeiro Jardim Mihnea Angheluţă 175 0 0 12 Mar 2025
Identifying Sub-networks in Neural Networks via Functionally Similar Representations Tian Gao Amit Dhurandhar Karthikeyan N. Ramamurthy Dennis L. Wei 89 0 0 21 Oct 2024
Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks Ann Huang Satpreet H. Singh Flavio Martinelli Kanaka Rajan 88 0 0 04 Oct 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks Clémentine Dominé Nicolas Anguita A. Proca Lukas Braun D. Kunin P. Mediano Andrew M. Saxe 115 6 0 22 Sep 2024
Relative Representations: Topological and Geometric Perspectives Alejandro García-Castellanos Giovanni Luca Marchetti Danica Kragic Martina Scolamiero 92 1 0 17 Sep 2024
When predict can also explain: few-shot prediction to select better neural latents Kabir V. Dabholkar Omri Barak BDL 118 0 0 23 May 2024
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 163 75 0 10 May 2023
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks Konstantin Schurholt Damian Borth 84 3 0 18 Jun 2020
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 168 561 0 30 Apr 2018
An Analysis of Neural Language Modeling at Multiple Scales Stephen Merity N. Keskar R. Socher 69 171 0 22 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 89 333 0 19 Mar 2018
A Tutorial on Canonical Correlation Methods Viivi Uurtio J. Monteiro J. Kandola John Shawe-Taylor D. Fernández-Reyes Juho Rousu CML 73 107 0 07 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 139 1,100 0 01 Nov 2017
Regularizing and Optimizing LSTM Language Models Stephen Merity N. Keskar R. Socher 173 1,096 0 07 Aug 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 138 1,829 0 16 Jun 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 158 1,526 1 19 Apr 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 356 4,636 0 10 Nov 2016
Pruning Filters for Efficient ConvNets Hao Li Asim Kadav Igor Durdanovic H. Samet H. Graf 3DPC 195 3,707 0 31 Aug 2016
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 318 6,715 0 08 Jun 2015
Visualizing and Understanding Recurrent Networks A. Karpathy Justin Johnson Li Fei-Fei HAI 132 1,102 0 05 Jun 2015