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The Expressive Power of a Class of Normalizing Flow Models

The Expressive Power of a Class of Normalizing Flow Models

31 May 2020
Zhifeng Kong
Kamalika Chaudhuri
    TPM
ArXivPDFHTML

Papers citing "The Expressive Power of a Class of Normalizing Flow Models"

14 / 14 papers shown
Title
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Probabilistic Forecasting of Irregular Time Series via Conditional Flows
Vijaya Krishna Yalavarthi
Randolf Scholz
Stefan Born
Lars Schmidt-Thieme
AI4TS
35
0
0
09 Feb 2024
Learning to Generate All Feasible Actions
Learning to Generate All Feasible Actions
Mirco Theile
Daniele Bernardini
Raphael Trumpp
C. Piazza
Marco Caccamo
Alberto L. Sangiovanni-Vincentelli
29
2
0
26 Jan 2023
Gradual Domain Adaptation via Normalizing Flows
Gradual Domain Adaptation via Normalizing Flows
Shogo Sagawa
H. Hino
CLL
OOD
22
10
0
23 Jun 2022
Variational Monte Carlo Approach to Partial Differential Equations with
  Neural Networks
Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks
M. Reh
M. Gärttner
27
8
0
04 Jun 2022
Flow-based Recurrent Belief State Learning for POMDPs
Flow-based Recurrent Belief State Learning for POMDPs
Xiaoyu Chen
Yao Mu
Ping Luo
Sheng Li
Jianyu Chen
45
18
0
23 May 2022
Universality of parametric Coupling Flows over parametric
  diffeomorphisms
Universality of parametric Coupling Flows over parametric diffeomorphisms
Junlong Lyu
Zhitang Chen
Chang Feng
Wenjing Cun
Shengyu Zhu
Yanhui Geng
Zhijie Xu
Yuhang Chen
16
3
0
07 Feb 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density
  Approximation
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
Emma R. Cobian
J. Hauenstein
Fang Liu
Daniele E. Schiavazzi
19
4
0
01 Feb 2022
Triangular Flows for Generative Modeling: Statistical Consistency,
  Smoothness Classes, and Fast Rates
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
N. J. Irons
M. Scetbon
Soumik Pal
Zaïd Harchaoui
33
17
0
31 Dec 2021
Sparse Flows: Pruning Continuous-depth Models
Sparse Flows: Pruning Continuous-depth Models
Lucas Liebenwein
Ramin Hasani
Alexander Amini
Daniela Rus
26
16
0
24 Jun 2021
Approximation capabilities of measure-preserving neural networks
Approximation capabilities of measure-preserving neural networks
Aiqing Zhu
Pengzhan Jin
Yifa Tang
29
8
0
21 Jun 2021
Riemannian Convex Potential Maps
Riemannian Convex Potential Maps
Samuel N. Cohen
Brandon Amos
Y. Lipman
25
22
0
18 Jun 2021
Score-based Generative Modeling in Latent Space
Score-based Generative Modeling in Latent Space
Arash Vahdat
Karsten Kreis
Jan Kautz
DiffM
16
659
0
10 Jun 2021
Jacobian Determinant of Normalizing Flows
Jacobian Determinant of Normalizing Flows
Huadong Liao
Jiawei He
DRL
19
7
0
12 Feb 2021
Convex Potential Flows: Universal Probability Distributions with Optimal
  Transport and Convex Optimization
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang
Ricky T. Q. Chen
Christos Tsirigotis
Aaron Courville
OT
119
95
0
10 Dec 2020
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