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1305.7255
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Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery
30 May 2013
Dominique Perraul-Joncas
M. Meilă
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Papers citing
"Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery"
22 / 22 papers shown
Reconstruction of Manifold Distances from Noisy Observations
Charles Fefferman
Jonathan Marty
Kevin Ren
42
0
0
17 Nov 2025
Learning collective variables that preserve transition rates
Shashank Sule
Arnav Mehta
Maria Cameron
295
0
0
02 Jun 2025
Cryo-em images are intrinsically low dimensional
Luke Evans
Octavian-Vlad Murad
Lars Dingeldein
Pilar Cossio
Roberto Covino
Marina Meila
AI4CE
442
2
0
15 Apr 2025
Manifold learning: what, how, and why
Annual Review of Statistics and Its Application (ARSIA), 2023
M. Meilă
Hanyu Zhang
283
130
0
07 Nov 2023
Principal subbundles for dimension reduction
M. Akhøj
J. Benn
E. Grong
Stefan Sommer
Xavier Pennec
210
1
0
06 Jul 2023
On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical Phenomena
International Conference on Sampling Theory and Applications (SampTA), 2023
Roy R. Lederman
B. Toader
DRL
311
4
0
27 Apr 2023
Effects of Data Geometry in Early Deep Learning
Neural Information Processing Systems (NeurIPS), 2022
Saket Tiwari
George Konidaris
423
8
0
29 Dec 2022
Staying the course: Locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds
Journal of Mathematical Chemistry (J. Math. Chem.), 2022
J. M. Bello-Rivas
Anastasia S. Georgiou
J. Guckenheimer
Ioannis G. Kevrekidis
272
3
0
21 Apr 2022
Nonlinear Isometric Manifold Learning for Injective Normalizing Flows
Eike Cramer
Felix Rauh
Alexander Mitsos
Raúl Tempone
Manuel Dahmen
DRL
220
9
0
08 Mar 2022
A singular Riemannian geometry approach to Deep Neural Networks I. Theoretical foundations
A. Benfenati
A. Marta
307
13
0
17 Dec 2021
Non-Parametric Manifold Learning
Electronic Journal of Statistics (EJS), 2021
D. Asta
270
0
0
16 Jul 2021
Learning Low-dimensional Manifolds for Scoring of Tissue Microarray Images
Donghui Yan
Jian Zou
Zhenpeng Li
141
0
0
22 Feb 2021
LOCA: LOcal Conformal Autoencoder for standardized data coordinates
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2020
Erez Peterfreund
Ofir Lindenbaum
Felix Dietrich
Tom S. Bertalan
M. Gavish
Ioannis G. Kevrekidis
Ronald R. Coifman
364
29
0
15 Apr 2020
Fitting a manifold of large reach to noisy data
Journal of Topology and Analysis (JTA) (JTA), 2019
Charles Fefferman
Sergei Ivanov
Matti Lassas
Hariharan Narayanan
551
29
0
11 Oct 2019
Knowledge Discovery In Nanophotonics Using Geometric Deep Learning
Advanced Intelligent Systems (AIS), 2019
Yashar Kiarashinejad
M. Zandehshahvar
Sajjad Abdollahramezani
Omid Hemmatyar
Reza Pourabolghasem
A. Adibi
199
98
0
16 Sep 2019
Selecting the independent coordinates of manifolds with large aspect ratios
Neural Information Processing Systems (NeurIPS), 2019
Yu-Chia Chen
M. Meilă
251
17
0
02 Jul 2019
Metric Learning on Manifolds
Max Aalto
Nakul Verma
135
3
0
05 Feb 2019
Manifold Coordinates with Physical Meaning
Samson Koelle
Hanyu Zhang
M. Meilă
Yu-Chia Chen
317
12
0
29 Nov 2018
Intrinsic Isometric Manifold Learning with Application to Localization
Ariel Schwartz
Ronen Talmon
173
20
0
01 Jun 2018
megaman: Manifold Learning with Millions of points
James McQueen
M. Meilă
J. Vanderplas
Zhongyue Zhang
168
11
0
09 Mar 2016
Improved graph Laplacian via geometric self-consistency
Neural Information Processing Systems (NeurIPS), 2014
Dominique C. Perrault-Joncas
M. Meilă
303
19
0
31 May 2014
Discussion of "Geodesic Monte Carlo on Embedded Manifolds"
Simon Byrne
Mark Girolami
P. Diaconis
C. Seiler
Susan P. Holmes
...
Marcelo Pereyra
Babak Shahbaba
Shiwei Lan
J. Streets
Daniel P. Simpson
257
0
0
05 Nov 2013
1
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