Convergent Learning: Do different neural networks learn the same representations?

24 November 2015

Jeff Clune

Papers citing "Convergent Learning: Do different neural networks learn the same representations?"

50 / 81 papers shown

Title
NeuRN: Neuro-inspired Domain Generalization for Image Classification Hamd Jalil Ahmed Qazi Asim Iqbal OOD MedIm 26 0 0 11 May 2025
Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry Mohammed Adnan Rohan Jain Ekansh Sharma Rahul Krishnan Yani Andrew Ioannou 56 0 0 08 May 2025
Representational Similarity via Interpretable Visual Concepts Neehar Kondapaneni Oisin Mac Aodha Pietro Perona DRL 201 0 0 19 Mar 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 76 5 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 49 0 0 12 Mar 2025
Forget the Data and Fine-Tuning! Just Fold the Network to Compress Dong Wang Haris Šikić Lothar Thiele O. Saukh 59 0 0 17 Feb 2025
Merging Feed-Forward Sublayers for Compressed Transformers Neha Verma Kenton W. Murray Kevin Duh AI4CE 50 0 0 10 Jan 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 133 0 0 30 Dec 2024
Process Reward Model with Q-Value Rankings W. Li Yixuan Li LRM 59 15 0 15 Oct 2024
Relative Representations: Topological and Geometric Perspectives Alejandro García-Castellanos G. Marchetti Danica Kragic Martina Scolamiero 50 0 0 17 Sep 2024
A Mechanistic Interpretation of Syllogistic Reasoning in Auto-Regressive Language Models Geonhee Kim Marco Valentino André Freitas LRM AI4CE 30 7 0 16 Aug 2024
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis Stefan Horoi Albert Manuel Orozco Camacho Eugene Belilovsky Guy Wolf FedML MoMe 32 9 0 07 Jul 2024
Latent Space Translation via Inverse Relative Projection Valentino Maiorca Luca Moschella Marco Fumero Francesco Locatello Emanuele Rodolà 42 1 0 21 Jun 2024
Neural Lineage Runpeng Yu Xinchao Wang 34 4 0 17 Jun 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models Nastaran Saadati Minh Pham Nasla Saleem Joshua R. Waite Aditya Balu Zhanhong Jiang Chinmay Hegde Soumik Sarkar MoMe 47 1 0 11 Apr 2024
Federated Learning over Connected Modes Dennis Grinwald Philipp Wiesner Shinichi Nakajima FedML 45 0 0 05 Mar 2024
Towards Meta-Pruning via Optimal Transport Alexander Theus Olin Geimer Friedrich Wicke Thomas Hofmann Sotiris Anagnostidis Sidak Pal Singh MoMe 24 3 0 12 Feb 2024
Do Vision and Language Encoders Represent the World Similarly? Mayug Maniparambil Raiymbek Akshulakov Y. A. D. Djilali Sanath Narayan M. Seddik K. Mangalam Noel E. O'Connor VLM 29 11 0 10 Jan 2024
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks Rahul Ramesh Ekdeep Singh Lubana Mikail Khona Robert P. Dick Hidenori Tanaka CoGe 39 7 0 21 Nov 2023
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems David A. Klindt Sophia Sanborn Francisco Acosta Frédéric Poitevin Nina Miolane MILM FAtt 44 7 0 17 Oct 2023
Investigating how ReLU-networks encode symmetries Georg Bökman Fredrik Kahl 29 6 0 26 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 58 64 0 10 May 2023
Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient Yuhang Li Youngeun Kim Hyoungseob Park Priyadarshini Panda 32 16 0 25 Apr 2023
On the Variance of Neural Network Training with respect to Test Sets and Distributions Keller Jordan OOD 24 11 0 04 Apr 2023
FastFill: Efficient Compatible Model Update Florian Jaeckle Fartash Faghri Ali Farhadi Oncel Tuzel Hadi Pouransari 36 2 0 08 Mar 2023
Testing the Channels of Convolutional Neural Networks Kang Choi Donghyun Son Younghoon Kim Jiwon Seo 28 1 0 06 Mar 2023
Analyzing Populations of Neural Networks via Dynamical Model Embedding Jordan S. Cotler Kai Sheng Tai Felipe Hernández Blake Elias David Sussillo 17 4 0 27 Feb 2023
Model Doctor for Diagnosing and Treating Segmentation Error Zhijie Jia Lin Chen Kaiwen Hu Lechao Cheng Zunlei Feng Min-Gyoo Song 26 0 0 17 Feb 2023
A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations Bilal Chughtai Lawrence Chan Neel Nanda 21 96 0 06 Feb 2023
Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov Andrei Filatov Teresa Yeo Ajay Sohmshetty Amir Zamir OOD 45 10 0 01 Dec 2022
ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah Sung Min Park Andrew Ilyas A. Madry SyDa 51 26 0 22 Nov 2022
REPAIR: REnormalizing Permuted Activations for Interpolation Repair Keller Jordan Hanie Sedghi O. Saukh R. Entezari Behnam Neyshabur MoMe 46 94 0 15 Nov 2022
GULP: a prediction-based metric between representations Enric Boix Adserà Hannah Lawrence George Stepaniants Philippe Rigollet 46 11 0 12 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels Daniel Shwartz Uri Stern D. Weinshall NoLa 36 2 0 02 Oct 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 63 11 0 21 Sep 2022
Random initialisations performing above chance and how to find them Frederik Benzing Simon Schug Robert Meier J. Oswald Yassir Akram Nicolas Zucchet Laurence Aitchison Angelika Steger ODL 35 24 0 15 Sep 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 255 316 0 11 Sep 2022
Knowledge Distillation of Transformer-based Language Models Revisited Chengqiang Lu Jianwei Zhang Yunfei Chu Zhengyu Chen Jingren Zhou Fei Wu Haiqing Chen Hongxia Yang VLM 27 10 0 29 Jun 2022
DORA: Exploring Outlier Representations in Deep Neural Networks Kirill Bykov Mayukh Deb Dennis Grinwald Klaus-Robert Muller Marina M.-C. Höhne 27 12 0 09 Jun 2022
What do CNNs Learn in the First Layer and Why? A Linear Systems Perspective Rhea Chowers Yair Weiss 33 2 0 06 Jun 2022
Representation Topology Divergence: A Method for Comparing Neural Network Representations S. Barannikov I. Trofimov Nikita Balabin Evgeny Burnaev 3DPC 40 45 0 31 Dec 2021
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability Sílvia Casacuberta Esra Suel Seth Flaxman FAtt 21 1 0 31 Dec 2021
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Zohar Ringel 35 51 0 31 Dec 2021
Forward Compatible Training for Large-Scale Embedding Retrieval Systems Vivek Ramanujan Pavan Kumar Anasosalu Vasu Ali Farhadi Oncel Tuzel Hadi Pouransari VLM 32 16 0 06 Dec 2021
ReAct: Out-of-distribution Detection With Rectified Activations Yiyou Sun Chuan Guo Yixuan Li OODD 43 456 0 24 Nov 2021
Efficient Decompositional Rule Extraction for Deep Neural Networks Mateo Espinosa Zarlenga Z. Shams M. Jamnik 14 16 0 24 Nov 2021
Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Konstantin Schurholt Dimche Kostadinov Damian Borth SSL 38 14 0 28 Oct 2021
Revisiting Model Stitching to Compare Neural Representations Yamini Bansal Preetum Nakkiran Boaz Barak FedML 44 105 0 14 Jun 2021
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 31 43 0 03 Jun 2021
Fast Adaptation with Linearized Neural Networks Wesley J. Maddox Shuai Tang Pablo G. Moreno A. Wilson Andreas C. Damianou 32 32 0 02 Mar 2021