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1605.08754
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Faster Eigenvector Computation via Shift-and-Invert Preconditioning
26 May 2016
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
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Papers citing
"Faster Eigenvector Computation via Shift-and-Invert Preconditioning"
50 / 2,354 papers shown
Energy-Inspired Models: Learning with Sampler-Induced Distributions
Neural Information Processing Systems (NeurIPS), 2019
Dieterich Lawson
George Tucker
Bo Dai
Rajesh Ranganath
295
32
0
31 Oct 2019
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis
Hal Daumé
Jennifer Wortman Vaughan
Hanna M. Wallach
XAI
FAtt
197
22
0
29 Oct 2019
On Investigation of Unsupervised Speech Factorization Based on Normalization Flow
Haoran Sun
Yunqi Cai
Lantian Li
Dong Wang
75
1
0
29 Oct 2019
Neural Density Estimation and Likelihood-free Inference
George Papamakarios
BDL
DRL
209
51
0
29 Oct 2019
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
Neural Information Processing Systems (NeurIPS), 2019
Maksim Kuznetsov
Daniil Polykovskiy
Dmitry Vetrov
Alexander Zhebrak
GAN
90
19
0
29 Oct 2019
Reversible designs for extreme memory cost reduction of CNN training
EURASIP Journal on Image and Video Processing (JIVP), 2019
T. Hascoet
Q. Febvre
Y. Ariki
T. Takiguchi
3DV
116
2
0
24 Oct 2019
Uncertainty Quantification with Generative Models
Vanessa Böhm
F. Lanusse
U. Seljak
173
29
0
22 Oct 2019
Markov Random Fields for Collaborative Filtering
Neural Information Processing Systems (NeurIPS), 2019
Harald Steck
154
29
0
21 Oct 2019
Unsupervised Out-of-Distribution Detection with Batch Normalization
Jiaming Song
Yang Song
Stefano Ermon
OODD
111
23
0
21 Oct 2019
Point Process Flows
Nazanin Mehrasa
Ruizhi Deng
Mohamed Osama Ahmed
B. Chang
Jiawei He
Thibaut Durand
Marcus A. Brubaker
Greg Mori
AI4TS
133
10
0
18 Oct 2019
Autoregressive Models: What Are They Good For?
Murtaza Dalal
Alexander C. Li
Rohan Taori
58
17
0
17 Oct 2019
Label-Conditioned Next-Frame Video Generation with Neural Flows
Sergey Tarasenko
VGen
94
1
0
16 Oct 2019
Conditional Invertible Flow for Point Cloud Generation
Michal Stypulkowski
M. Zamorski
Maciej Ziȩba
J. Chorowski
3DPC
92
15
0
16 Oct 2019
Target-Oriented Deformation of Visual-Semantic Embedding Space
Takashi Matsubara
149
7
0
15 Oct 2019
Understanding the Limitations of Variational Mutual Information Estimators
International Conference on Learning Representations (ICLR), 2019
Jiaming Song
Stefano Ermon
SSL
DRL
265
232
0
14 Oct 2019
Imitating by generating: deep generative models for imitation of interactive tasks
Frontiers in Robotics and AI (Front. Robot. AI), 2019
Judith Butepage
Ali Ghadirzadeh
Özge Öztimur Karadag
Mårten Björkman
Danica Kragic
101
31
0
14 Oct 2019
Powering Hidden Markov Model by Neural Network based Generative Models
European Conference on Artificial Intelligence (ECAI), 2019
Dong Liu
Antoine Honoré
Saikat Chatterjee
L. Rasmussen
BDL
264
15
0
13 Oct 2019
Distilling Importance Sampling for Likelihood Free Inference
Journal of Computational And Graphical Statistics (JCGS), 2019
D. Prangle
Cecilia Viscardi
371
5
0
08 Oct 2019
MIM: Mutual Information Machine
M. Livne
Kevin Swersky
David J. Fleet
DRL
196
8
0
08 Oct 2019
FIS-GAN: GAN with Flow-based Importance Sampling
Shiyu Yi
Donglin Zhan
Wenqing Zhang
Zhengyang Geng
Kang An
Hao Wang
GAN
227
3
0
06 Oct 2019
High Mutual Information in Representation Learning with Symmetric Variational Inference
M. Livne
Kevin Swersky
David J. Fleet
SSL
DRL
128
0
0
04 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of State Space Models
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
Tom Ryder
D. Prangle
Andrew Golightly
Isaac Matthews
BDL
AI4TS
300
8
0
02 Oct 2019
Graph Generation with Variational Recurrent Neural Network
Shih-Yang Su
Shunwei Lei
Greg Mori
GAN
GNN
167
18
0
02 Oct 2019
Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
Jonas Köhler
Leon Klein
Frank Noé
207
102
0
02 Oct 2019
Neural Canonical Transformation with Symplectic Flows
Physical Review X (PRX), 2019
Shuo-Hui Li
Chen Dong
Linfeng Zhang
Lei Wang
DRL
429
29
0
30 Sep 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
R. Cornish
M. Volkovs
George Deligiannidis
Arnaud Doucet
148
2
0
30 Sep 2019
Hamiltonian Generative Networks
International Conference on Learning Representations (ICLR), 2019
Peter Toth
Danilo Jimenez Rezende
Andrew Jaegle
S. Racanière
Aleksandar Botev
I. Higgins
BDL
DRL
AI4CE
GAN
240
231
0
30 Sep 2019
Equivariant Hamiltonian Flows
Danilo Jimenez Rezende
S. Racanière
I. Higgins
Peter Toth
168
67
0
30 Sep 2019
Graph Residual Flow for Molecular Graph Generation
Shion Honda
Hirotaka Akita
Katsuhiko Ishiguro
Toshiki Nakanishi
Kenta Oono
129
44
0
30 Sep 2019
Automated curricula through setter-solver interactions
S. Racanière
Andrew Kyle Lampinen
Adam Santoro
David P. Reichert
Vlad Firoiu
Timothy Lillicrap
249
59
0
27 Sep 2019
Identifying through Flows for Recovering Latent Representations
International Conference on Learning Representations (ICLR), 2019
Shen Li
Bryan Hooi
Gim Hee Lee
DRL
OOD
242
14
0
27 Sep 2019
Towards neural networks that provably know when they don't know
International Conference on Learning Representations (ICLR), 2019
Alexander Meinke
Matthias Hein
OODD
283
147
0
26 Sep 2019
Intensity-Free Learning of Temporal Point Processes
International Conference on Learning Representations (ICLR), 2019
Oleksandr Shchur
Marin Bilos
Stephan Günnemann
AI4TS
276
200
0
26 Sep 2019
CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarios
Wenhao Ding
Mengdi Xu
Ding Zhao
182
61
0
17 Sep 2019
Flow Models for Arbitrary Conditional Likelihoods
International Conference on Machine Learning (ICML), 2019
Yongqian Li
Shoaib Akbar
Junier B. Oliva
OOD
AI4CE
182
42
0
13 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
International Conference on Learning Representations (ICLR), 2019
Uyeong Jang
Susmit Jha
S. Jha
AAML
274
14
0
07 Sep 2019
Set Flow: A Permutation Invariant Normalizing Flow
Kashif Rasul
Ingmar Schuster
Roland Vollgraf
Urs M. Bergmann
BDL
3DPC
DRL
135
6
0
06 Sep 2019
Video Interpolation and Prediction with Unsupervised Landmarks
Kevin J. Shih
Aysegül Dündar
Animesh Garg
R. Pottorf
Andrew Tao
Bryan Catanzaro
101
6
0
06 Sep 2019
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Xuezhe Ma
Chunting Zhou
Xian Li
Graham Neubig
Eduard H. Hovy
AI4TS
BDL
235
199
0
05 Sep 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning
Astrophysical Journal (ApJ), 2019
Johann Brehmer
S. Mishra-Sharma
Joeri Hermans
Gilles Louppe
Kyle Cranmer
413
80
0
04 Sep 2019
Towards Interpretable Polyphonic Transcription with Invertible Neural Networks
International Society for Music Information Retrieval Conference (ISMIR), 2019
Rainer Kelz
Gerhard Widmer
108
15
0
04 Sep 2019
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps
Benjamin Hou
Athanasios Vlontzos
A. Alansary
Daniel Rueckert
Bernhard Kainz
MedIm
115
1
0
29 Aug 2019
PixelVAE++: Improved PixelVAE with Discrete Prior
Hossein Sadeghi
Evgeny Andriyash
W. Vinci
L. Buffoni
Mohammad H. Amin
BDL
DRL
143
33
0
26 Aug 2019
Normalizing Flows: An Introduction and Review of Current Methods
I. Kobyzev
S. Prince
Marcus A. Brubaker
TPM
MedIm
239
58
0
25 Aug 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction
Apratim Bhattacharyya
M. Hanselmann
Mario Fritz
Bernt Schiele
C. Straehle
BDL
DRL
AI4TS
225
93
0
24 Aug 2019
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks
Juan Maroñas
Roberto Paredes Palacios
D. Ramos-Castro
UQCV
BDL
249
28
0
23 Aug 2019
Noise Flow: Noise Modeling with Conditional Normalizing Flows
IEEE International Conference on Computer Vision (ICCV), 2019
A. Abdelhamed
Marcus A. Brubaker
M. S. Brown
204
190
0
22 Aug 2019
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
IEEE International Conference on Computer Vision (ICCV), 2019
Haoliang Sun
Ronak R. Mehta
H. Zhou
Z. Huang
Sterling C. Johnson
V. Prabhakaran
Vikas Singh
MedIm
182
53
0
21 Aug 2019
Modeling the Gaia Color-Magnitude Diagram with Bayesian Neural Flows to Constrain Distance Estimates
M. Cranmer
Richard Galvez
L. Anderson
D. Spergel
S. Ho
159
8
0
21 Aug 2019
Survey on Deep Neural Networks in Speech and Vision Systems
M. Alam
Manar D. Samad
Lasitha Vidyaratne
Alexander M. Glandon
Khan M. Iftekharuddin
3DV
VLM
AI4TS
371
226
0
16 Aug 2019
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