Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth

29 October 2020

Thao Nguyen

Papers citing "Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth"

50 / 64 papers shown

Title
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades Yanan Li Fanxu Meng Muhan Zhang Shiai Zhu Shangguang Wang Mengwei Xu MoMe 2 0 0 17 May 2025
DiGIT: Multi-Dilated Gated Encoder and Central-Adjacent Region Integrated Decoder for Temporal Action Detection Transformer Ho-Joong Kim Y. E. Lee Jung-Ho Hong Seong-Whan Lee 47 0 0 09 May 2025
Advancing 3D Medical Image Segmentation: Unleashing the Potential of Planarian Neural Networks in Artificial Intelligence Ziyuan Huang Kevin Huggins Srikar Bellur 3DV 54 0 0 07 May 2025
Representational Similarity via Interpretable Visual Concepts Neehar Kondapaneni Oisin Mac Aodha Pietro Perona DRL 219 0 0 19 Mar 2025
A super-resolution reconstruction method for lightweight building images based on an expanding feature modulation network Yi Zhang Wenye Zhou Ruonan Lin SupR 65 0 0 17 Mar 2025
Measuring Error Alignment for Decision-Making Systems Binxia Xu Antonis Bikakis Daniel Onah A. Vlachidis Luke Dickens 41 0 0 03 Jan 2025
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations Lorenzo Basile Santiago Acevedo Luca Bortolussi Fabio Anselmi Alex Rodriguez 48 4 0 22 Jun 2024
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge into Visual Semantic Segmentation for Autonomous Driving Sicen Guo Zhiyuan Wu Qijun Chen Ioannis Pitas Rui Fan Rui Fan 40 1 0 13 Mar 2024
What Do Self-Supervised Speech and Speaker Models Learn? New Findings From a Cross Model Layer-Wise Analysis Takanori Ashihara Marc Delcroix Takafumi Moriya Kohei Matsuura Taichi Asami Yusuke Ijima SSL 24 7 0 31 Jan 2024
ExpPoint-MAE: Better interpretability and performance for self-supervised point cloud transformers Ioannis Romanelis Vlassis Fotis Konstantinos Moustakas Adrian Munteanu ViT 3DPC 28 4 0 19 Jun 2023
Efficient Mixed Transformer for Single Image Super-Resolution Ling Zheng Jinchen Zhu Jinpeng Shi Shizhuang Weng 40 19 0 19 May 2023
Multi-Path Transformer is Better: A Case Study on Neural Machine Translation Ye Lin Shuhan Zhou Yanyang Li Anxiang Ma Tong Xiao Jingbo Zhu 38 0 0 10 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures Max Klabunde Tobias Schumacher M. Strohmaier Florian Lemmerich 58 66 0 10 May 2023
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models D. Honegger Konstantin Schurholt Damian Borth 35 4 0 26 Apr 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
Revisiting the Evaluation of Image Synthesis with GANs Mengping Yang Ceyuan Yang Yichi Zhang Qingyan Bai Yujun Shen Bo Dai EGVM 41 7 0 04 Apr 2023
The Framework Tax: Disparities Between Inference Efficiency in NLP Research and Deployment Jared Fernandez Jacob Kahn Clara Na Yonatan Bisk Emma Strubell FedML 33 10 0 13 Feb 2023
FlexiViT: One Model for All Patch Sizes Lucas Beyer Pavel Izmailov Alexander Kolesnikov Mathilde Caron Simon Kornblith Xiaohua Zhai Matthias Minderer Michael Tschannen Ibrahim M. Alabdulmohsin Filip Pavetić VLM 45 90 0 15 Dec 2022
On the effectiveness of partial variance reduction in federated learning with heterogeneous data Bo-wen Li Mikkel N. Schmidt T. S. Alstrøm Sebastian U. Stich FedML 37 9 0 05 Dec 2022
ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah Sung Min Park Andrew Ilyas A. Madry SyDa 54 26 0 22 Nov 2022
On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning S. Takagi OffRL 18 7 0 17 Nov 2022
Boosting vision transformers for image retrieval Chull Hwan Song Jooyoung Yoon Shunghyun Choi Yannis Avrithis ViT 34 32 0 21 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation Olivier Laurent Adrien Lafage Enzo Tartaglione Geoffrey Daniel Jean-Marc Martinez Andrei Bursuc Gianni Franchi OODD 46 32 0 17 Oct 2022
When does deep learning fail and how to tackle it? A critical analysis on polymer sequence-property surrogate models Himanshu T. Patra AI4CE 15 0 0 12 Oct 2022
Boosting Graph Neural Networks via Adaptive Knowledge Distillation Zhichun Guo Chunhui Zhang Yujie Fan Yijun Tian Chuxu Zhang Nitesh V. Chawla 26 32 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
Model Zoos: A Dataset of Diverse Populations of Neural Network Models Konstantin Schurholt Diyar Taskiran Boris Knyazev Xavier Giró-i-Nieto Damian Borth 60 29 0 29 Sep 2022
MAC: A Meta-Learning Approach for Feature Learning and Recombination S. Tiwari M. Gogoi S. Verma K. P. Singh CLL 37 1 0 20 Sep 2022
Git Re-Basin: Merging Models modulo Permutation Symmetries Samuel K. Ainsworth J. Hayase S. Srinivasa MoMe 255 318 0 11 Sep 2022
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing Naresh Gurulingan Elahe Arani Bahram Zonooz 24 1 0 19 Aug 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 23 124 0 27 Jul 2022
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks Andrew M. Saxe Shagun Sodhani Sam Lewallen AI4CE 32 34 0 21 Jul 2022
Large-scale Robustness Analysis of Video Action Recognition Models Madeline Chantry Schiappa Naman Biyani Prudvi Kamtam Shruti Vyas Hamid Palangi Vibhav Vineet Yogesh S Rawat AAML 37 24 0 04 Jul 2022
Neural Networks as Paths through the Space of Representations Richard D. Lange Devin Kwok Jordan K Matelsky Xinyue Wang David Rolnick Konrad Paul Kording 37 4 0 22 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
A Closer Look at Self-Supervised Lightweight Vision Transformers Shaoru Wang Jin Gao Zeming Li Jian Sun Weiming Hu ViT 73 42 0 28 May 2022
On the Symmetries of Deep Learning Models and their Internal Representations Charles Godfrey Davis Brown Tegan H. Emerson Henry Kvinge 28 40 0 27 May 2022
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks Zhiwei Bai Tao Luo Z. Xu Yaoyu Zhang 31 5 0 26 May 2022
When does dough become a bagel? Analyzing the remaining mistakes on ImageNet Vijay Vasudevan Benjamin Caine Raphael Gontijo-Lopes Sara Fridovich-Keil Rebecca Roelofs VLM UQCV 48 57 0 09 May 2022
Explaining the Effectiveness of Multi-Task Learning for Efficient Knowledge Extraction from Spine MRI Reports Arijit Sehanobish M. Sandora Nabila Abraham Jayashri Pawar Danielle Torres Anasuya Das M. Becker Richard Herzog Benjamin Odry Ron Vianu 21 3 0 06 May 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 45 127 0 11 Apr 2022
Universal Representations: A Unified Look at Multiple Task and Domain Learning Wei-Hong Li Xialei Liu Hakan Bilen SSL OOD 30 27 0 06 Apr 2022
Online Convolutional Re-parameterization Mu Hu Junyi Feng Jiashen Hua Baisheng Lai Jianqiang Huang Xiaojin Gong Xiansheng Hua 24 26 0 02 Apr 2022
What Makes Transfer Learning Work For Medical Images: Feature Reuse & Other Factors Christos Matsoukas Johan Fredin Haslum Moein Sorkhei Magnus P Soderberg Kevin Smith VLM OOD MedIm 27 85 0 02 Mar 2022
On the Origins of the Block Structure Phenomenon in Neural Network Representations Thao Nguyen M. Raghu Simon Kornblith 25 14 0 15 Feb 2022
How Do Vision Transformers Work? Namuk Park Songkuk Kim ViT 47 466 0 14 Feb 2022
Investigating Power laws in Deep Representation Learning Arna Ghosh Arnab Kumar Mondal Kumar Krishna Agrawal Blake A. Richards SSL OOD 14 19 0 11 Feb 2022
Deconfounded Representation Similarity for Comparison of Neural Networks Tianyu Cui Yogesh Kumar Pekka Marttinen Samuel Kaski CML 35 13 0 31 Jan 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