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Normalizing Flows: An Introduction and Review of Current Methods

Normalizing Flows: An Introduction and Review of Current Methods

25 August 2019
I. Kobyzev
S. Prince
Marcus A. Brubaker
    TPM
    MedIm
ArXivPDFHTML

Papers citing "Normalizing Flows: An Introduction and Review of Current Methods"

13 / 13 papers shown
Title
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
Pierre Marion
Anna Korba
Peter Bartlett
Mathieu Blondel
Valentin De Bortoli
Arnaud Doucet
Felipe Llinares-López
Courtney Paquette
Quentin Berthet
79
12
0
08 Feb 2024
Normalizing Flow based Hidden Markov Models for Classification of Speech
  Phones with Explainability
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability
Anubhab Ghosh
Antoine Honoré
Dong Liu
G. Henter
S. Chatterjee
16
5
0
01 Jul 2021
Robust Classification using Hidden Markov Models and Mixtures of
  Normalizing Flows
Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows
Anubhab Ghosh
Antoine Honoré
Dong Liu
G. Henter
S. Chatterjee
BDL
VLM
35
7
0
15 Feb 2021
On the Sentence Embeddings from Pre-trained Language Models
On the Sentence Embeddings from Pre-trained Language Models
Bohan Li
Hao Zhou
Junxian He
Mingxuan Wang
Yiming Yang
Lei Li
13
213
0
02 Nov 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy
A Neural Network MCMC sampler that maximizes Proposal Entropy
Zengyi Li
Yubei Chen
Friedrich T. Sommer
25
14
0
07 Oct 2020
Deep composition of tensor-trains using squared inverse Rosenblatt
  transports
Deep composition of tensor-trains using squared inverse Rosenblatt transports
Tiangang Cui
S. Dolgov
OT
26
33
0
14 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep
  learning
Relative gradient optimization of the Jacobian term in unsupervised deep learning
Luigi Gresele
G. Fissore
Adrián Javaloy
Bernhard Schölkopf
Aapo Hyvarinen
DRL
19
22
0
26 Jun 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang
Fei-Yue Wang
BDL
28
280
0
17 Jun 2020
Categorical Normalizing Flows via Continuous Transformations
Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe
E. Gavves
BDL
21
43
0
17 Jun 2020
Learned Factor Graphs for Inference from Stationary Time Sequences
Learned Factor Graphs for Inference from Stationary Time Sequences
Nir Shlezinger
Nariman Farsad
Yonina C. Eldar
Andrea J. Goldsmith
21
24
0
05 Jun 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows
  and Latent Variable Models
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models
Chin-Wei Huang
Laurent Dinh
Aaron Courville
DRL
31
87
0
17 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph
  Generation
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi
Minkai Xu
Zhaocheng Zhu
Weinan Zhang
Ming Zhang
Jian Tang
64
425
0
26 Jan 2020
Cubic-Spline Flows
Cubic-Spline Flows
Conor Durkan
Artur Bekasov
Iain Murray
George Papamakarios
TPM
48
57
0
05 Jun 2019
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