Testing the manifold hypothesis

Cited by (425)

Items 301–400 of 425

1. On Extensions of e Diffeomorphisms
   Steven B. Damelin, Charles Fefferman · 2015 · arXiv (Cornell University)
2. On the Whitney distortion extension problem for $C^m(\mathbb R^n)$ and $C^{\infty}(\mathbb R^n)$ and its applications to interpolation and alignment of data in $\mathbb R^n$
   Steven B. Damelin, Charles Fefferman · 2015 · arXiv (Cornell University)
3. Data analysis from empirical moments and the Christoffel function
   Edouard Pauwels, Mihai Putinar, Jean Bernard Lasserre · 2018 · arXiv (Cornell University)
4. Topology and Neural Networks
   Mustafa Hajij, Kyle Istvan · 2020 · arXiv (Cornell University)
5. Testing and Emulating Modified Gravity on Cosmological Scales
   Andrius Tamosiunas · 2020 · arXiv (Cornell University)
6. On the Whitney extension problem for near isometries and beyond.
   Steven B. Damelin · 2021 · arXiv (Cornell University)
7. Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms
   Holden, Matthew, Marcelo Pereyra, Konstantinos C. Zygalakis · 2021 · arXiv (Cornell University)
8. Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
   Elen Vardanyan, Sona Hunanyan, Galstyan, Tigran, Arshak Minasyan, Arnak S. Dalalyan · 2023 · arXiv (Cornell University)
9. Myoelectric Hand Gesture Recognition using Variational Autoencoder and Sensor Fusion
   Keith Currier, Jirui Fu, Nasrin Bayat, Yanjie Fu, Jong-Hwan Kim, Joon‐Hyuk Park · 2024 · Research Square
10. Data-driven modelling of ground-based and space-based telescope's point spread functions
    T.I Liaudat · 2022
11. Audiovisual speech representation learning applied to emotion recognition
    Samir Sadok · 2024 · theses.fr (ABES)
12. Differential Similarity in Higher Dimensional Spaces: Theory and Applications
    L. Thorne McCarty · 2019 · arXiv (Cornell University)
13. Discretized Gradient Flow for Manifold Learning in the Space of Embeddings
    Dara Gold, Steven Rosenberg · 2019 · arXiv (Cornell University)
14. Power Weighted Shortest Paths for Unsupervised Learning.
    Daniel H. McKenzie, Steven B. Damelin · 2019 · arXiv (Cornell University)
15. Manifold Fitting in Ambient Space
    Zhigang Yao, Li, Bingjie, Tan, Wee Chin · 2019 · arXiv (Cornell University)
16. OCSVM-based Evaluation Method for Generative Neural Networks
    Artur Istvan Karoly, Márta Takács, Péter Galambos · 2019 · International Joint Conference on Neural Networks (IJCNN)
17. A generic unfolding algorithm for manifolds estimated by local linear approximations
    Jonas Nordhaug Myhre, Matineh Shaker, Mustafa Devrim Kaba, Robert Jenssen, Deniz Erdogmus B · 2020 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
18. Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
    Stefan C. Schonsheck · 2020 · arXiv (Cornell University)
19. Encoded Prior Sliced Wasserstein AutoEncoder for learning latent manifold representations
    Sanjukta Krishnagopal, Jacob Bedrossian · 2020 · arXiv (Cornell University)
20. Manifold-based time series forecasting
    Nikita Puchkin, Aleksandr Timofeev, Vladimir Grigor'evich Spokoiny · 2020 · arXiv (Cornell University)
21. Black-box model risk in finance
    SN Cohen, Daniel Snow, Łukasz Szpruch · 2021 · arXiv (Cornell University)
22. Quadric Hypersurface Intersection for Manifold Learning in Feature Space
    Fedor Pavutnitskiy, Sergei Olegovich Ivanov, Abramov, Evgeny, Viacheslav Borovitskiy, Artem Klochkov, Viktor Vyalov, Anatolii Zaikovskii, Aleksandr Petiushko · 2021 · arXiv (Cornell University)
23. Topological Deep Learning: Classification Neural Networks
    Mustafa Hajij, Kyle Istvan · 2021 · arXiv (Cornell University)
24. 28910 Wissen über Raum und Zeit
    Diedrich Wolter, Özgür Lütfü Özçep · 2026
25. Multi-chart flows.
    Dimitris Kalatzis, Johan Ziruo Ye, Jesper Wohlert, Søren Hauberg · 2021 · arXiv (Cornell University)
26. On Matrix Factorizations in Subspace Clustering
    Reeshad Arian, Keaton Hamm · 2021 · arXiv (Cornell University)
27. Meta-Parameter Selection for Embedding Generation of Latency Spaces in Auto Encoder Analytics
    Maria Walch, Peter Schichtel, Dirk Joachim Lehmann, Amala Paulson · 2021 · International Conference on Time Series and Forecasting (ITISE)
28. Emergence of Deep Machine Learning in Medicine
    Richard Dybowski · 2021 · Springer eBooks
29. Reconstruction and interpolation of manifolds II: Inverse problems for Riemannian manifolds with partial distance data
    Charles Fefferman, Sergei Ivanov, Matti J. Lassas, Jinpeng Lu, Hariharan Narayanan · 2021 · arXiv (Cornell University)
30. A machine learning-based representation of the electron density in biomacromolecules
    Bruno Cuevas-Zuviría · 2021
31. Emergence of Deep Machine Learning in Medicine
    Richard Dybowski · 2022 · Springer eBooks
32. A Metric Space for Point Process Excitations
    Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan · 2022 · Journal of Artificial Intelligence Research
33. Learning Machine Reasoning for Bioactivity Prediction of Chemicals
    Suman Chakravarti · 2020 · ChemRxiv
34. Geometry in Optimization
    Robert Simon Fong, Peter Tiňo B · 2022 · Studies in computational intelligence
35. Spectral aspects of mining complex networks
    Leo Torres · 2021 · Digital Repository Service (Northeastern University)
36. Augmented Feature Generation Using Maximum Mutual Information Minimum Correlation
    Arghya Kusum Das, Saptarsi Goswami, Amit Kumar Das, Amlan Chakrabarti, Basabi Chakraborty · 2022 · Lecture notes on data engineering and communications technologies
37. Deciding on a Continuum of Equivalent Alternatives Engaging Uncertainty through Behavior Patterning
    Kusal Rathnayake, А.Н. Лебедев, Dimitri Volchenkov · 2022 · Foundations
38. Identifying latent distances with Finslerian geometry
    Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg · 2022 · arXiv (Cornell University)
39. Preserving Data Manifold Structure in Latent Space for Exploration through Network Geodesics
    Sanjukta Krishnagopal, Jacob Bedrossian · 2022 · International Joint Conference on Neural Networks (IJCNN)
40. Pointless Topology
    A. A. Cavia, Patricia Reed · 2023 · AI critique
41. Isometric Manifold Learning Using Hierarchical Flow
    Ziqi Pan, Jianfu Zhang, Li Niu, Liqing Zhang · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
42. Generative A.I. helps extract ecological meaning from the complex three dimensional shapes of bird bills
    Russell Dinnage, Marian Kleineberg · 2023
43. EACA 2022. XVII Encuentro de Álgebra Computacional y Aplicaciones. XVII Meeting on Computer algebra and Applications
    Julio José Moyano‐Fernández, Carlos Galindo, Philippe Giménez, Fernando Hernando, Francisco Monserrat · 2023 · Universitat Jaume I eBooks
44. Is My Neural Net Driven by the MDL Principle?
    Eduardo Brandão, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban · 2023 · Lecture notes in computer science
45. Machine learning methods applied to COVID-19 patient data
    Vitor P. Bezzan · 2021
46. Algebraic machine learning with an application to chemistry
    Ezzeddine El Sai, Parker Gara, Markus J. Pflaum · 2024 · Foundations of Data Science
47. Unsupervised metric learning via K-ISOMAP for high-dimensional data clustering
    Rodrigo de P. Mendes, Gustavo Henrique Chavari, Alexandre L. M. Levada · 2024 · Research Square
48. Statistical Optimal Transport and its Entropic Regularization: Compared and Contrasted
    Shayan Hundrieser · 2024
49. Deep Convolutional Neural Network Compression based on the Intrinsic Dimension of the Training Data
    Abir Mohammad Hadi, Kwanghee Won · 2024 · ACM SIGAPP Applied Computing Review
50. Low-dimensional intrinsic dimension reveals a phase transition in gradient-based learning of deep neural networks
    Chengli Tan, Jiangshe Zhang, Junmin Liu, Zixiang Zhao · 2024 · International Journal of Machine Learning and Cybernetics
51. Automated Test Case Generation Based on Path Structure Matrix and Mainfold-Inspired Search
    Caijie Guo, Yan Tang, Xiaobing Li, Peihao Ding · 2024 · International Conference on Computer Supported Cooperative Work in Design (CSCWD)
52. Learning Internal Representations of 3D Transformations From 2D Projected Inputs
    Marissa Connor, Bruno A. Olshausen, Christopher J. Rozell · 2024 · Neural Computation
53. Dimensionality-Induced Information Loss of Outliers in Deep Neural Networks
    Kazuki Uematsu, Kosuke Haruki, Taiji Suzuki, Mitsuhiro Kimura, Takahiro Takimoto, Hideyuki Nakagawa · 2024 · Lecture notes in computer science
54. Taming the curse of dimensionality: quantitative economics with deep learning
    Jesús Fernández‐Villaverde, Galo Nuño, Jesse Perla · 2024 · Documentos de trabajo/Documento de trabajo - Banco de España, Servicio de Estudios
55. Generalized compression and compressive search of large datasets
    Morgan E. Prior, Thomas J. Howard, Emily Light, Najib Ishaq, Noah M. Daniels · 2024 · IEEE International Conference on Big Data (BigData)
56. Optimal Approximation of Smooth Functions on Riemannian Manifolds Using Deep Relu Neural Networks
    Demetrio Labate A, Ji Shi · 2025 · SSRN Electronic Journal
57. Power Transformed Density Ridge Estimation
    Hengchao Chen, Zheng Zhai · 2025 · IEEE Signal Processing Letters
58. Cluster Based Association Measures with Applications
    Sabyasachi Bera, Farnaz Fouladi, Shyamal Peddada · 2025 · Sankhya B
59. Almost Optimal PAC Learning for 𝑘-Means
    Vincent Cohen-Addad, Silvio Lattanzi, Chris Schwiegelshohn · 2025 · ACM Symposium on Theory of Computing (STOC)
60. Representation of Two-Dimensional (2D) Geometric Shape Quality
    Qiang Huang · 2025 · Springer eBooks
61. Face and voice cross-modal association with learning convex feature embedding
    Taewan Kim, Jiwoo Kang · 2025 · Multimedia Systems
62. Monotone Generative Modeling via a Gromov–Monge Embedding
    Wonjun Lee, Yifei Yang, Dongmian Zou, Gilad Lerman · 2025 · SIAM Journal on Mathematics of Data Science
63. Normalized Space Alignment: A Versatile Metric for Representation Analysis
    Danish Ebadulla, Aditya Gulati, Ambuj K. Singh · 2025 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
64. Geometric sparsification in recurrent neural networks
    Wyatt Mackey, Ioannis D. Schizas, Jared Deighton, David L. Boothe, Vasileios Maroulas · 2025 · npj Artificial Intelligence
65. Latent Manifold Reconstruction and Representation with Topological and Geometrical Regularization
    Ren Wang, Pengcheng Zhou · 2025 · Lecture notes in computer science
66. Identification of Distinct Topological Structures From High-Dimensional Data
    Bingxian Xu, Rosemary Braun · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
67. Preliminary Analysis on Dynamics Equation Discovery with Locally Structured Unitary Network
    Motoyasu Suzuki, Shogo Muramatsu · 2025 · International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)
68. Leveraging Synthetic Adult Datasets for Unsupervised Infant Pose Estimation
    Sarosij Bose, Hannah Dela Cruz, Arindam Dutta, Elena Kokkoni, Konstantinos Karydis, Amit K. Roy–Chowdhury · 2025 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
69. A Manifold Framework for Interpretable Brain Age Estimation and Aging Trajectory Mapping
    Zifei Liang, Collin James Szczepanski, Chenyang Li, Jiayi Li, Henry Rusinek, Yulin Ge, Jiangyang Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
70. Sigma Flows for Image and Data Labeling and Learning Structured Prediction
    Jonas Cassel, Bastian Boll, Stefania Petra, Peter Albers, Christoph Schnörr · 2025 · Journal of Mathematical Imaging and Vision
71. Approximate Fiber Products of Schemes and Their Étale Homotopical Invariants
    Dongfang Zhao · 2025 · Mathematics
72. Data-driven material identification in heterogeneous viscoelastic media
    Hossein Salahshoor, M. Ortíz, Laurent Stainier · 2026 · Journal of the Mechanics and Physics of Solids
73. Flow-aware ellipsoidal filtration for persistent homology of recurrent signals
    Omer Bahadir Eryilmaz, Cihan Katar, Max A. Little · 2026 · Chaos An Interdisciplinary Journal of Nonlinear Science
74. Efficient Manifold-Constrained Neural ODE for High-Dimensional Datasets
    Muhao Guo, Haoran Li, Yang Weng · 2025 · International Joint Conference on Neural Networks (IJCNN)
75. High-Fidelity Transcriptome Reconstruction of Degraded RNA-Seq Samples Using Denoising Diffusion Models
    Ke Xiao, Jinlei Sun, Yunqing Liu, Chen Li, Hengchuan Guo, Yiying Wang, Yajun Pang, Zhiyu Liu · 2025 · Biology
76. Nonasymptotic bounds for forward processes in denoising diffusions: Ornstein–Uhlenbeck is hard to beat
    Miha Brešar, Aleksandar Mijatović · 2025 · The Annals of Applied Probability
77. New horizons in machine understanding: explanatory and objectual understanding in deep learning video generation models
    Pierre Beckmann · 2025 · Synthese
78. Integral Betti signatures of brain, climate and financial networks compared to hyperbolic, Euclidean and spherical models
    Luigi Caputi, Anna Pidnebesna, Jaroslav Hlinka · 2025 · Scientific Reports
79. Structured Universal Adversarial Attacks on Object Detection for Video Sequences
    Sven Jacob, Weijia Shao, Gjergji Kasneci · 2026 · Lecture notes in computer science
80. Gaussian universality in neural network dynamics with generalized structured input distributions
    Jaeyong Bae, Hawoong Jeong · 2026 · Journal of Statistical Mechanics Theory and Experiment
81. Method of Moments for Estimation of Noisy Curves
    Phillip Lo, Yuehaw Khoo · 2026 · SIAM Journal on Mathematics of Data Science
82. Derivative Training for Robust Image Regression
    Vsevolod I. Avrutskiy · 2026 · SSRN Electronic Journal
83. Osculating geometry and higher‐order distance Loci
    Sandra Di Rocco, Kemal Rose, Luca Sodomaco · 2026 · Journal of the London Mathematical Society
84. Implicit dynamics identification in time-varying manifolds using Laplace-Beltrami dynamic mode decomposition
    Tongzhen Dang, Weiyang Ding · 2026 · Journal of Computational and Applied Mathematics
85. On the impact of pretraining data ordering in transformer encoder- and decoder-only language models
    Luca Dini, Lucia Domenichelli, Dominique Brunato⋄, Felice Dell’Orletta⋄ · 2026 · Knowledge-Based Systems
86. An Approach to Fisher-Rao Metric for Infinite Dimensional Non-Parametric Information Geometry
    Bing Cheng, Howell Tong · 2026 · Entropy
87. Low-dimensional continuous attractors in recurrent neural networks : from statistical physics to computational neuroscience
    Aldo Battista · 2020 · theses.fr (ABES)
88. Generative Adversarial Networks : theory and practice
    Ugo Tanielian · 2021 · theses.fr (ABES)
89. Meaningful audio synthesis and musical interactions by representation learning of sound sample databases
    Adrien Bitton · 2021 · theses.fr (ABES)
90. Exploration et modélisation de données peu ou pas structurées
    Vincent Grollemund · 2021 · theses.fr (ABES)
91. Modèles à Variables Latentes Profonds : des propriétés aux structures
    Victor Berger · 2021 · theses.fr (ABES)
92. A study of some trade-offs in statistical learning : online learning, generative models and fairness
    Nicolas Schreuder · 2021 · theses.fr (ABES)
93. Online machine learning-based predictive maintenance for the railway industry
    Minh Huong Le Nguyen · 2023 · theses.fr (ABES)
94. Low-rank and sparse approximations for contact mechanics
    Kiran Sagar Kollepara · 2022
95. Joint deconvolution and semi & unsupervised component separation, with application to radio-interferometry
    Rémi Carloni Gertosio · 2022
96. Learning multi-modal distributions and image editing with deep generative models
    Thibaut Issenhuth · 2023 · theses.fr (ABES)
97. Mechanical submodels driven by machine learning : application to structural dynamics
    Hamza Boukraichi · 2023 · theses.fr (ABES)
98. Complexity Methods in Physics-Guided Machine Learning
    Eduardo Brandão · 2023 · theses.fr (ABES)
99. Surrogate models based on large eddy simulations and deep learning for coaxial rocket engine injector design
    José Felix Zapata Usandivaras · 2024 · theses.fr (ABES)
100. Learning the dynamics of multispectral satellite image time series
     Anthony Frion · 2024 · theses.fr (ABES)