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Deep Networks and the Multiple Manifold Problem

25 August 2020

Papers citing "Deep Networks and the Multiple Manifold Problem"

31 / 31 papers shown

Title
A Theoretical Study of Neural Network Expressive Power via Manifold Topology Jiachen Yao Mayank Goswami Chao Chen 52 0 0 21 Oct 2024
Quantum Kernel Methods under Scrutiny: A Benchmarking Study Jan Schnabel M. Roth 97 8 0 06 Sep 2024
Hardness of Learning Neural Networks under the Manifold Hypothesis B. Kiani Jason Wang Melanie Weber 67 4 0 03 Jun 2024
Better than classical? The subtle art of benchmarking quantum machine learning models Joseph Bowles Shahnawaz Ahmed Maria Schuld 100 76 0 11 Mar 2024
Defining Neural Network Architecture through Polytope Structures of Dataset Sangmin Lee Abbas Mammadov Jong Chul Ye 91 1 0 04 Feb 2024
Upper and lower bounds for the Lipschitz constant of random neural networks Paul Geuchen Thomas Heindl Dominik Stöger Felix Voigtlaender AAML 69 0 0 02 Nov 2023
On the Disconnect Between Theory and Practice of Neural Networks: Limits of the NTK Perspective Jonathan Wenger Felix Dangel Agustinus Kristiadi 83 0 0 29 Sep 2023
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 56 6 0 06 Jun 2023
Data Representations' Study of Latent Image Manifolds Ilya Kaufman Omri Azencot 62 8 0 31 May 2023
Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization Cameron Jakub Mihai Nica ODL 23 5 0 20 Feb 2023
Topological Learning in Multi-Class Data Sets Christopher H. Griffin Trevor K. Karn Benjamin Apple AI4CE 60 0 0 23 Jan 2023
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces Saket Tiwari Omer Gottesman George Konidaris 63 0 0 29 Dec 2022
Effects of Data Geometry in Early Deep Learning Saket Tiwari George Konidaris 148 7 0 29 Dec 2022
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 377 50 0 29 Sep 2022
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence Yi Ma Doris Y. Tsao H. Shum 138 78 0 11 Jul 2022
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime Benjamin Bowman Guido Montúfar 70 15 0 06 Jun 2022
The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization Mufan Li Mihai Nica Daniel M. Roy 92 39 0 06 Jun 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization Simone Bombari Mohammad Hossein Amani Marco Mondelli 83 26 0 20 May 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 59 11 0 19 Apr 2022
Fitting an immersed submanifold to data via Sussmann's orbit theorem Joshua Hanson Maxim Raginsky 59 4 0 03 Apr 2022
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers Guodong Zhang Aleksandar Botev James Martens OffRL 80 28 0 15 Mar 2022
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization Mariia Seleznova Gitta Kutyniok 229 20 0 01 Feb 2022
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs Ido Nachum Jan Hkazla Michael C. Gastpar Anatoly Khina 55 0 0 03 Nov 2021
Deep Networks Provably Classify Data on Curves Tingran Wang Sam Buchanan D. Gilboa John N. Wright 71 9 0 29 Jul 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 76 78 0 28 Jun 2021
The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization Mufan Li Mihai Nica Daniel M. Roy 110 34 0 07 Jun 2021
Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks Hancheng Min Salma Tarmoun René Vidal Enrique Mallada MLT 76 5 0 13 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 88 204 0 06 May 2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements Tian Tong Cong Ma Ashley Prater-Bennette Erin E. Tripp Yuejie Chi 93 33 0 29 Apr 2021
Generalized Approach to Matched Filtering using Neural Networks Jingkai Yan Mariam Avagyan R. Colgan D. Veske I. Bartos John N. Wright Z. Márka S. Márka 36 21 0 08 Apr 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks Quynh N. Nguyen Marco Mondelli Guido Montúfar 84 83 0 21 Dec 2020