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"

34 / 84 papers shown

Title
Representation Topology Divergence: A Method for Comparing Neural Network Representations S. Barannikov I. Trofimov Nikita Balabin Evgeny Burnaev 3DPC 28 45 0 31 Dec 2021
Does MAML Only Work via Feature Re-use? A Data Centric Perspective Brando Miranda Yu-xiong Wang Oluwasanmi Koyejo 30 4 0 24 Dec 2021
When Neural Networks Using Different Sensors Create Similar Features Hugues Moreau A. Vassilev Liming Luke Chen 25 0 0 04 Nov 2021
Context Meta-Reinforcement Learning via Neuromodulation Eseoghene Ben-Iwhiwhu Jeffery Dick Nicholas A. Ketz Praveen K. Pilly Andrea Soltoggio OffRL 30 12 0 30 Oct 2021
Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Konstantin Schurholt Dimche Kostadinov Damian Borth SSL 19 14 0 28 Oct 2021
Don't speak too fast: The impact of data bias on self-supervised speech models Yen Meng Yi-Hui Chou Andy T. Liu Hung-yi Lee 34 25 0 15 Oct 2021
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models Robert Wolfe Aylin Caliskan 85 51 0 01 Oct 2021
Do Vision Transformers See Like Convolutional Neural Networks? M. Raghu Thomas Unterthiner Simon Kornblith Chiyuan Zhang Alexey Dosovitskiy ViT 52 924 0 19 Aug 2021
Layer-wise Analysis of a Self-supervised Speech Representation Model Ankita Pasad Ju-Chieh Chou Karen Livescu SSL 26 287 0 10 Jul 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 39 155 0 17 Jun 2021
Revisiting Model Stitching to Compare Neural Representations Yamini Bansal Preetum Nakkiran Boaz Barak FedML 32 104 0 14 Jun 2021
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis Zihang Meng Rudrasis Chakraborty Vikas Singh 9 9 0 08 Jun 2021
Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition Yihong Dong Ying Peng Muqiao Yang Songtao Lu Qingjiang Shi 40 9 0 05 Jun 2021
Is BERT a Cross-Disciplinary Knowledge Learner? A Surprising Finding of Pre-trained Models' Transferability Wei-Tsung Kao Hung-yi Lee 16 16 0 12 Mar 2021
Aggregative Self-Supervised Feature Learning from a Limited Sample Jiuwen Zhu Yuexiang Li S. Kevin Zhou SSL 22 0 0 14 Dec 2020
Learn to Bind and Grow Neural Structures Azhar Shaikh Nishant Sinha CLL 16 0 0 21 Nov 2020
For self-supervised learning, Rationality implies generalization, provably Yamini Bansal Gal Kaplun Boaz Barak OOD SSL 58 22 0 16 Oct 2020
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics V. Ramasesh Ethan Dyer M. Raghu CLL 24 173 0 14 Jul 2020
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks Konstantin Schurholt Damian Borth 24 3 0 18 Jun 2020
High-contrast "gaudy" images improve the training of deep neural network models of visual cortex Benjamin R. Cowley Jonathan W. Pillow 18 10 0 13 Jun 2020
Critical Assessment of Transfer Learning for Medical Image Segmentation with Fully Convolutional Neural Networks Davood Karimi Simon K. Warfield Ali Gholipour MedIm 14 19 0 30 May 2020
How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents Richard Meyes Moritz Schneider Tobias Meisen 20 2 0 07 Apr 2020
Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations Richard Meyes Constantin Waubert de Puiseau Andres Felipe Posada-Moreno Tobias Meisen AI4CE 30 22 0 02 Apr 2020
Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability Robin Hirt Akash Srivastava Carlos Berg Niklas Kühl 8 3 0 29 Mar 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 38 120 0 26 Mar 2020
Similarity of Neural Networks with Gradients Shuai Tang Wesley J. Maddox Charlie Dickens Tom Diethe Andreas C. Damianou 14 25 0 25 Mar 2020
AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks Majed El Helou Frederike Dumbgen Sabine Süsstrunk CLL AI4CE 24 2 0 07 Mar 2020
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs Matthew L. Leavitt Ari S. Morcos 58 33 0 03 Mar 2020
Robust Training with Ensemble Consensus Jisoo Lee Sae-Young Chung NoLa 17 28 0 22 Oct 2019
Modelling the influence of data structure on learning in neural networks: the hidden manifold model Sebastian Goldt M. Mézard Florent Krzakala Lenka Zdeborová BDL 21 51 0 25 Sep 2019
Investigating Multilingual NMT Representations at Scale Sneha Kudugunta Ankur Bapna Isaac Caswell N. Arivazhagan Orhan Firat LRM 141 120 0 05 Sep 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 20 1,354 0 01 May 2019
Shared Representational Geometry Across Neural Networks Qihong Lu Po-Hsuan Chen Jonathan W. Pillow Peter J. Ramadge K. A. Norman Uri Hasson OOD 16 11 0 28 Nov 2018
How deep is deep enough? -- Quantifying class separability in the hidden layers of deep neural networks Junhong Lin C. Metzner Andreas K. Maier V. Cevher Holger Schulze Patrick Krauss 18 56 0 05 Nov 2018