LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood

29 June 2022

Papers citing "LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood"

26 / 26 papers shown

Title
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 76 7 0 31 Oct 2024
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows Willem Diepeveen Georgios Batzolis Zakhar Shumaylov Carola-Bibiane Schönlieb DiffM 43 2 0 02 Oct 2024
Intrinsic Dimensionality Estimation within Tight Localities: A Theoretical and Experimental Analysis Laurent Amsaleg Oussama Chelly Michael E. Houle Ken-ichi Kawarabayashi Miloš Radovanović Weeris Treeratanajaru 46 50 0 29 Sep 2022
Scikit-dimension: a Python package for intrinsic dimension estimation Jonathan Bac Evgeny M. Mirkes Alexander N. Gorban I. Tyukin A. Zinovyev 56 82 0 06 Sep 2021
Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows Brendan Leigh Ross Jesse C. Cresswell TPM 47 32 0 09 Jun 2021
Rectangular Flows for Manifold Learning Anthony L. Caterini Gabriel Loaiza-Ganem Geoff Pleiss John P. Cunningham DRL 36 44 0 02 Jun 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 219 264 0 18 Apr 2021
Maximum Likelihood Training of Score-Based Diffusion Models Yang Song Conor Durkan Iain Murray Stefano Ermon DiffM 78 642 0 22 Jan 2021
Flows for simultaneous manifold learning and density estimation Johann Brehmer Kyle Cranmer DRL AI4CE 63 157 0 31 Mar 2020
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 83 761 0 10 Jun 2019
Intrinsic dimension of data representations in deep neural networks A. Ansuini Alessandro Laio Jakob H. Macke D. Zoccolan AI4CE 36 269 0 29 May 2019
Estimating the effective dimension of large biological datasets using Fisher separability analysis L. Albergante Jonathan Bac A. Zinovyev 57 38 0 18 Jan 2019
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis G. B. Cavallari Leo Sampaio Ferraz Ribeiro M. Ponti SSL OOD DRL 16 29 0 01 Nov 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 179 3,110 0 09 Jul 2018
Measuring the Intrinsic Dimension of Objective Landscapes Chunyuan Li Heerad Farkhoor Rosanne Liu J. Yosinski 54 407 0 24 Apr 2018
Estimating the intrinsic dimension of datasets by a minimal neighborhood information Elena Facco M. d’Errico Alex Rodriguez Alessandro Laio 19 320 0 19 Mar 2018
On the Latent Space of Wasserstein Auto-Encoders Paul Kishan Rubenstein Bernhard Schölkopf Ilya O. Tolstikhin DRL 15 52 0 11 Feb 2018
Wasserstein Auto-Encoders Ilya O. Tolstikhin Olivier Bousquet Sylvain Gelly B. Schölkopf DRL 90 1,049 0 05 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 90 8,807 0 25 Aug 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 92 1,340 0 19 May 2017
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 221 4,143 0 21 May 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 175 8,351 0 28 Nov 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 69 2,246 0 30 Oct 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 319 16,972 0 20 Dec 2013
Testing the Manifold Hypothesis Charles Fefferman S. Mitter Hariharan Narayanan 66 523 0 01 Oct 2013
Popular Ensemble Methods: An Empirical Study R. Maclin D. Opitz 91 2,965 0 01 Jun 2011