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UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

9 February 2018
Leland McInnes
John Healy
James Melville
ArXivPDFHTML

Papers citing "UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction"

16 / 116 papers shown
Title
Beyond Predictions in Neural ODEs: Identification and Interventions
Beyond Predictions in Neural ODEs: Identification and Interventions
H. Aliee
Fabian J. Theis
Niki Kilbertus
CML
73
24
0
23 Jun 2021
The Language Interpretability Tool: Extensible, Interactive
  Visualizations and Analysis for NLP Models
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
Ian Tenney
James Wexler
Jasmijn Bastings
Tolga Bolukbasi
Andy Coenen
...
Ellen Jiang
Mahima Pushkarna
Carey Radebaugh
Emily Reif
Ann Yuan
VLM
101
192
0
12 Aug 2020
An Investigation of the Weight Space to Monitor the Training Progress of
  Neural Networks
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks
Konstantin Schurholt
Damian Borth
50
3
0
18 Jun 2020
Deep Learning Multidimensional Projections
Deep Learning Multidimensional Projections
M. Espadoto
N. Hirata
A. Telea
30
63
0
21 Feb 2019
Manifold Learning of Four-dimensional Scanning Transmission Electron
  Microscopy
Manifold Learning of Four-dimensional Scanning Transmission Electron Microscopy
Xin Li
Ondrej Dyck
M. Oxley
A. Lupini
Leland McInnes
John Healy
S. Jesse
Sergei V. Kalinin
18
48
0
18 Oct 2018
(Self-Attentive) Autoencoder-based Universal Language Representation for
  Machine Translation
(Self-Attentive) Autoencoder-based Universal Language Representation for Machine Translation
Carlos Escolano
Marta R. Costa-jussá
José A. R. Fonollosa
SSL
35
7
0
15 Oct 2018
Deep convolutional Gaussian processes
Deep convolutional Gaussian processes
Kenneth Blomqvist
Samuel Kaski
Markus Heinonen
BDL
53
60
0
06 Oct 2018
Data-Driven Design: Exploring new Structural Forms using Machine
  Learning and Graphic Statics
Data-Driven Design: Exploring new Structural Forms using Machine Learning and Graphic Statics
Lukas Fuhrimann
V. Moosavi
P. Ohlbrock
Pierluigi Dacunto
AI4CE
24
20
0
23 Sep 2018
Gaussian mixture models with Wasserstein distance
Gaussian mixture models with Wasserstein distance
Benoit Gaujac
Ilya Feige
David Barber
21
9
0
12 Jun 2018
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
G. Linderman
M. Rachh
J. Hoskins
Stefan Steinerberger
Y. Kluger
56
435
0
25 Dec 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
168
8,807
0
25 Aug 2017
Clustering with t-SNE, provably
Clustering with t-SNE, provably
G. Linderman
Stefan Steinerberger
25
226
0
08 Jun 2017
Visualizing Large-scale and High-dimensional Data
Visualizing Large-scale and High-dimensional Data
Jian Tang
J. Liu
Ming Zhang
Qiaozhu Mei
AI4TS
36
378
0
01 Feb 2016
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
291
33,445
0
16 Oct 2013
A Survey on Metric Learning for Feature Vectors and Structured Data
A Survey on Metric Learning for Feature Vectors and Structured Data
A. Bellet
Amaury Habrard
M. Sebban
95
680
0
28 Jun 2013
Classifying Clustering Schemes
Classifying Clustering Schemes
Gunnar Carlsson
Facundo Mémoli
72
93
0
24 Nov 2010
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