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Diagnosing and Fixing Manifold Overfitting in Deep Generative Models

14 April 2022

Papers citing "Diagnosing and Fixing Manifold Overfitting in Deep Generative Models"

21 / 21 papers shown

Title
Learning geometry and topology via multi-chart flows Hanlin Yu Søren Hauberg Marcelo Hartmann Arto Klami Georgios Arvanitidis AI4CE 49 0 0 30 May 2025
Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity Ziqiang Liu Wei Zhang Tiejun Li DiffM 77 0 0 15 May 2025
Demystifying Diffusion Policies: Action Memorization and Simple Lookup Table Alternatives Chengyang He Xu Liu Gadiel Sznaier Camps Guillaume Sartoretti Mac Schwager 80 1 0 09 May 2025
A Geometric Framework for Understanding Memorization in Generative Models Brendan Leigh Ross Hamidreza Kamkari Tongzi Wu Rasa Hosseinzadeh Zhaoyan Liu George Stein Jesse C. Cresswell Gabriel Loaiza-Ganem 154 9 0 31 Oct 2024
Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion Enrico Ventura Beatrice Achilli Gianluigi Silvestri Carlo Lucibello L. Ambrogioni DiffM 135 10 0 08 Oct 2024
Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection Yewen Li Chaojie Wang Xiaobo Xia Xu He Ruyi An Dong Li Tongliang Liu Bo An Xinrun Wang OODD 88 0 0 05 Sep 2024
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models Hamidreza Kamkari Brendan Leigh Ross Rasa Hosseinzadeh Jesse C. Cresswell Gabriel Loaiza-Ganem DiffM 106 16 0 05 Jun 2024
Metric Flow Matching for Smooth Interpolations on the Data Manifold Kacper Kapusniak Peter Potaptchik Teodora Reu Leo Zhang Alexander Tong Michael M. Bronstein A. Bose Francesco Di Giovanni 89 22 0 23 May 2024
A Geometric Explanation of the Likelihood OOD Detection Paradox Hamidreza Kamkari Brendan Leigh Ross Jesse C. Cresswell M. Volkovs Rahul G. Krishnan Gabriel Loaiza-Ganem OODD 101 12 0 27 Mar 2024
MINDE: Mutual Information Neural Diffusion Estimation Giulio Franzese Mustapha Bounoua Pietro Michiardi DiffM 80 8 0 13 Oct 2023
Graph-level Representation Learning with Joint-Embedding Predictive Architectures Geri Skenderi Hang Li Jiliang Tang Marco Cristani AI4TS GNN 159 5 0 27 Sep 2023
Multi-modal Latent Diffusion Mustapha Bounoua Giulio Franzese Pietro Michiardi DiffM 98 13 0 07 Jun 2023
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models Ba-Hien Tran Giulio Franzese Pietro Michiardi Maurizio Filippone DiffM 134 4 0 30 May 2023
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation Zhaoyan Liu Noël Vouitsis S. Gorti Jimmy Ba Gabriel Loaiza-Ganem ViT 75 1 0 26 Apr 2023
Diffusion Model-Augmented Behavioral Cloning Shangcheng Chen Hsiang-Chun Wang Ming-Hao Hsu Chun-Mao Lai Shao-Hua Sun DiffM 153 31 0 26 Feb 2023
Denoising Deep Generative Models Gabriel Loaiza-Ganem Brendan Leigh Ross Luhuan Wu John P. Cunningham Jesse C. Cresswell M. Volkovs DiffM 106 5 0 30 Nov 2022
CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds Jesse C. Cresswell Brendan Leigh Ross Gabriel Loaiza-Ganem H. Reyes-González Marco Letizia M. Volkovs 86 38 0 23 Nov 2022
Verifying the Union of Manifolds Hypothesis for Image Data Bradley Brown M. Volkovs Brendan Leigh Ross Jesse C. Cresswell Gabriel Loaiza-Ganem 139 43 0 06 Jul 2022
Neural Implicit Manifold Learning for Topology-Aware Density Estimation Brendan Leigh Ross Gabriel Loaiza-Ganem M. Volkovs Jesse C. Cresswell AI4CE 77 3 0 22 Jun 2022
Deterministic training of generative autoencoders using invertible layers Gianluigi Silvestri Daan Roos L. Ambrogioni TPM 79 2 0 19 May 2022
Spread Flows for Manifold Modelling Mingtian Zhang Yitong Sun Chen Zhang Jingyu Sun AI4CE 63 2 0 29 Sep 2021