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Sum-of-Squares Polynomial Flow

Sum-of-Squares Polynomial Flow

7 May 2019
P. Jaini
Kira A. Selby
Yaoliang Yu
    TPM
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Papers citing "Sum-of-Squares Polynomial Flow"

29 / 29 papers shown
Title
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
I. Butakov
Alexander Sememenko
Alexander Tolmachev
Andrey Gladkov
Marina Munkhoeva
Alexey Frolov
37
0
0
09 Oct 2024
ISR: Invertible Symbolic Regression
ISR: Invertible Symbolic Regression
Tony Tohme
M. J. Khojasteh
Mohsen Sadr
Florian Meyer
Kamal Youcef-Toumi
51
0
0
10 May 2024
A Review of Change of Variable Formulas for Generative Modeling
A Review of Change of Variable Formulas for Generative Modeling
Ullrich Kothe
21
6
0
04 Aug 2023
Normalizing Flow with Variational Latent Representation
Normalizing Flow with Variational Latent Representation
Hanze Dong
Shizhe Diao
Weizhong Zhang
Tong Zhang
BDL
OOD
DRL
13
0
0
21 Nov 2022
Beyond Hawkes: Neural Multi-event Forecasting on Spatio-temporal Point
  Processes
Beyond Hawkes: Neural Multi-event Forecasting on Spatio-temporal Point Processes
Negar Erfanian
Santiago Segarra
Maarten V. de Hoop
AI4TS
16
1
0
05 Nov 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows
Whitening Convergence Rate of Coupling-based Normalizing Flows
Felix Dräxler
Christoph Schnörr
Ullrich Kothe
36
7
0
25 Oct 2022
Neural PCA for Flow-Based Representation Learning
Neural PCA for Flow-Based Representation Learning
Shen Li
Bryan Hooi
DRL
13
1
0
23 Aug 2022
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing
  Flows
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows
Difeng Cai
Yuliang Ji
Huan He
Q. Ye
Yuanzhe Xi
TPM
28
4
0
05 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
24
8
0
04 Jun 2022
Short-Term Density Forecasting of Low-Voltage Load using
  Bernstein-Polynomial Normalizing Flows
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows
M. Arpogaus
Marcus Voss
Beate Sick
Mark Nigge-Uricher
Oliver Durr
28
15
0
29 Apr 2022
Multivariate Quantile Function Forecaster
Multivariate Quantile Function Forecaster
Kelvin K. Kan
Franccois-Xavier Aubet
Tim Januschowski
Youngsuk Park
Konstantinos Benidis
Lars Ruthotto
Jan Gasthaus
AI4TS
39
22
0
23 Feb 2022
Spherical Poisson Point Process Intensity Function Modeling and
  Estimation with Measure Transport
Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport
T. L. J. Ng
A. Zammit‐Mangion
24
3
0
24 Jan 2022
Hierarchical Conditional Flow: A Unified Framework for Image
  Super-Resolution and Image Rescaling
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
Christos Sakaridis
Andreas Lugmayr
Peng Sun
Martin Danelljan
Luc Van Gool
Radu Timofte
48
102
0
11 Aug 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
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
41
481
0
08 Mar 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
Self Normalizing Flows
Self Normalizing Flows
Thomas Anderson Keller
Jorn W. T. Peters
P. Jaini
Emiel Hoogeboom
Patrick Forré
Max Welling
30
14
0
14 Nov 2020
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Jason J. Yu
Konstantinos G. Derpanis
Marcus A. Brubaker
TPM
32
41
0
26 Oct 2020
Improving Sequential Latent Variable Models with Autoregressive Flows
Improving Sequential Latent Variable Models with Autoregressive Flows
Joseph Marino
Lei Chen
Jiawei He
Stephan Mandt
BDL
AI4TS
30
12
0
07 Oct 2020
Variational Inference with Continuously-Indexed Normalizing Flows
Variational Inference with Continuously-Indexed Normalizing Flows
Anthony L. Caterini
R. Cornish
Dino Sejdinovic
Arnaud Doucet
BDL
24
19
0
10 Jul 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural
  Networks
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks
Jens Behrmann
Paul Vicol
Kuan-Chieh Jackson Wang
Roger C. Grosse
J. Jacobsen
23
92
0
16 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows
The Convolution Exponential and Generalized Sylvester Flows
Emiel Hoogeboom
Victor Garcia Satorras
Jakub M. Tomczak
Max Welling
25
28
0
02 Jun 2020
Relaxing Bijectivity Constraints with Continuously Indexed Normalising
  Flows
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
R. Cornish
Anthony L. Caterini
George Deligiannidis
Arnaud Doucet
22
2
0
30 Sep 2019
Intensity-Free Learning of Temporal Point Processes
Intensity-Free Learning of Temporal Point Processes
Oleksandr Shchur
Marin Bilos
Stephan Günnemann
AI4TS
27
167
0
26 Sep 2019
Unconstrained Monotonic Neural Networks
Unconstrained Monotonic Neural Networks
Antoine Wehenkel
Gilles Louppe
TPM
28
146
0
14 Aug 2019
Stochastic Neural Network with Kronecker Flow
Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang
Ahmed Touati
Pascal Vincent
Gintare Karolina Dziugaite
Alexandre Lacoste
Aaron Courville
BDL
24
8
0
10 Jun 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation
  and Bayesian Inference
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference
Jakob Kruse
Gianluca Detommaso
Ullrich Kothe
Robert Scheichl
13
45
0
25 May 2019
Iterative Gaussianization: from ICA to Random Rotations
Iterative Gaussianization: from ICA to Random Rotations
Valero Laparra
Gustavo Camps-Valls
Jesús Malo
64
125
0
31 Jan 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
251
2,550
0
25 Jan 2016
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