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Neural Autoregressive Flows

Neural Autoregressive Flows

3 April 2018
Chin-Wei Huang
David M. Krueger
Alexandre Lacoste
Aaron Courville
    DRL
    AI4CE
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Papers citing "Neural Autoregressive Flows"

50 / 97 papers shown
Title
Accelerate TarFlow Sampling with GS-Jacobi Iteration
Accelerate TarFlow Sampling with GS-Jacobi Iteration
Ben Liu
Zhen Qin
2
0
0
19 May 2025
Towards Hierarchical Rectified Flow
Towards Hierarchical Rectified Flow
Yichi Zhang
Yici Yan
A. Schwing
Zhizhen Zhao
52
1
0
24 Feb 2025
Bayesian Adaptive Calibration and Optimal Design
Bayesian Adaptive Calibration and Optimal Design
Rafael Oliveira
Dino Sejdinovic
David Howard
Edwin Bonilla
113
0
0
20 Jan 2025
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
Joint Identifiability of Cross-Domain Recommendation via Hierarchical
  Subspace Disentanglement
Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement
Jing Du
Zesheng Ye
Bin Guo
Zhiwen Yu
Lina Yao
36
1
0
06 Apr 2024
Sequential Flow Straightening for Generative Modeling
Sequential Flow Straightening for Generative Modeling
Jongmin Yoon
Juho Lee
29
0
0
09 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks
Ruigang Wang
Krishnamurthy Dvijotham
I. Manchester
36
5
0
02 Feb 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models
Sample, estimate, aggregate: A recipe for causal discovery foundation models
Menghua Wu
Yujia Bao
Regina Barzilay
Tommi Jaakkola
CML
49
7
0
02 Feb 2024
Efficient and Generalized end-to-end Autonomous Driving System with
  Latent Deep Reinforcement Learning and Demonstrations
Efficient and Generalized end-to-end Autonomous Driving System with Latent Deep Reinforcement Learning and Demonstrations
Zuojin Tang
Xiaoyu Chen
YongQiang Li
Jianyu Chen
24
2
0
22 Jan 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
On Learning the Tail Quantiles of Driving Behavior Distributions via
  Quantile Regression and Flows
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
Jia Yu Tee
Oliver De Candido
Wolfgang Utschick
Philipp Geiger
27
0
0
22 May 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
Uzma Hasan
Emam Hossain
Md. Osman Gani
CML
AI4TS
33
24
0
27 Mar 2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of
  Generative AI from GAN to ChatGPT
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Yihan Cao
Siyu Li
Yixin Liu
Zhiling Yan
Yutong Dai
Philip S. Yu
Lichao Sun
29
507
0
07 Mar 2023
Evaluating Robustness and Uncertainty of Graph Models Under Structural
  Distributional Shifts
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
Gleb Bazhenov
Denis Kuznedelev
A. Malinin
Artem Babenko
Liudmila Prokhorenkova
OOD
19
3
0
27 Feb 2023
Identifiability of latent-variable and structural-equation models: from
  linear to nonlinear
Identifiability of latent-variable and structural-equation models: from linear to nonlinear
Aapo Hyvarinen
Ilyes Khemakhem
R. Monti
CML
30
41
0
06 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality
A Survey of Methods, Challenges and Perspectives in Causality
Gael Gendron
Michael Witbrock
Gillian Dobbie
OOD
AI4CE
CML
29
12
0
01 Feb 2023
HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN
HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN
Adam Kania
Artur Kasymov
Maciej Ziȩba
Przemysław Spurek
38
9
0
27 Jan 2023
Proximal Residual Flows for Bayesian Inverse Problems
Proximal Residual Flows for Bayesian Inverse Problems
J. Hertrich
BDL
TPM
36
4
0
30 Nov 2022
Finding mixed-strategy equilibria of continuous-action games without
  gradients using randomized policy networks
Finding mixed-strategy equilibria of continuous-action games without gradients using randomized policy networks
Carlos Martin
T. Sandholm
28
11
0
29 Nov 2022
Waveflow: Enforcing boundary conditions in smooth normalizing flows with
  application to fermionic wave functions
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions
Luca Thiede
Chong Sun
A. Aspuru‐Guzik
31
1
0
27 Nov 2022
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
CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning
  with Demonstrations
CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations
Kai Yan
A. Schwing
Yu-xiong Wang
OffRL
30
2
0
18 Oct 2022
Modular Flows: Differential Molecular Generation
Modular Flows: Differential Molecular Generation
Yogesh Verma
Samuel Kaski
Markus Heinonen
Vikas K. Garg
29
14
0
12 Oct 2022
Connecting Surrogate Safety Measures to Crash Probablity via Causal
  Probabilistic Time Series Prediction
Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction
Jiajian Lu
Offer Grembek
M. Hansen
AI4TS
19
0
0
04 Oct 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian
  Preserving Flows
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
G. Morel
Lucas Drumetz
Simon Benaïchouche
Nicolas Courty
F. Rousseau
OT
30
6
0
22 Sep 2022
Maximum Likelihood on the Joint (Data, Condition) Distribution for
  Solving Ill-Posed Problems with Conditional Flow Models
Maximum Likelihood on the Joint (Data, Condition) Distribution for Solving Ill-Posed Problems with Conditional Flow Models
John Shelton Hyatt
8
1
0
24 Aug 2022
AdaCat: Adaptive Categorical Discretization for Autoregressive Models
AdaCat: Adaptive Categorical Discretization for Autoregressive Models
Qiyang Li
Ajay Jain
Pieter Abbeel
OffRL
45
4
0
03 Aug 2022
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network
Vitaliy Chiley
Vithursan Thangarasa
Abhay Gupta
Anshul Samar
Joel Hestness
D. DeCoste
50
8
0
28 Jun 2022
Modular Conformal Calibration
Modular Conformal Calibration
Charles Marx
Shengjia Zhao
W. Neiswanger
Stefano Ermon
34
15
0
23 Jun 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
NFL: Robust Learned Index via Distribution Transformation
NFL: Robust Learned Index via Distribution Transformation
Shangyu Wu
Yufei Cui
Jinghuan Yu
Xuan Sun
Tei-Wei Kuo
Chun Jason Xue
OOD
20
25
0
24 May 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
43
18
0
23 May 2022
COMET Flows: Towards Generative Modeling of Multivariate Extremes and
  Tail Dependence
COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence
Andrew McDonald
Pang-Ning Tan
Lifeng Luo
21
9
0
02 May 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal
  Optimization adjoint with Moving Speed
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed
Shian Du
Yihong Luo
Wei Chen
Jian Xu
Delu Zeng
32
7
0
19 Mar 2022
Differentiable Causal Discovery Under Latent Interventions
Differentiable Causal Discovery Under Latent Interventions
Gonccalo R. A. Faria
André F. T. Martins
Mário A. T. Figueiredo
BDL
CML
OOD
45
23
0
04 Mar 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
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
Generalized Normalizing Flows via Markov Chains
Generalized Normalizing Flows via Markov Chains
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDL
DiffM
AI4CE
30
22
0
24 Nov 2021
Diffusion Normalizing Flow
Diffusion Normalizing Flow
Qinsheng Zhang
Yongxin Chen
DiffM
26
87
0
14 Oct 2021
Generating Smooth Pose Sequences for Diverse Human Motion Prediction
Generating Smooth Pose Sequences for Diverse Human Motion Prediction
Wei Mao
Miaomiao Liu
Mathieu Salzmann
3DH
27
74
0
19 Aug 2021
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
Insights from Generative Modeling for Neural Video Compression
Insights from Generative Modeling for Neural Video Compression
Ruihan Yang
Yibo Yang
Joseph Marino
Stephan Mandt
VGen
35
16
0
28 Jul 2021
A Survey on Neural Speech Synthesis
A Survey on Neural Speech Synthesis
Xu Tan
Tao Qin
Frank Soong
Tie-Yan Liu
AI4TS
18
352
0
29 Jun 2021
On Incorporating Inductive Biases into VAEs
On Incorporating Inductive Biases into VAEs
Ning Miao
Emile Mathieu
N. Siddharth
Yee Whye Teh
Tom Rainforth
CML
DRL
27
10
0
25 Jun 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
23
8
0
21 Jun 2021
A deep generative model for probabilistic energy forecasting in power
  systems: normalizing flows
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
Jonathan Dumas
Antoine Wehenkel
Bertrand Cornélusse
Antonio Sutera
AI4TS
32
82
0
17 Jun 2021
Marginalizable Density Models
Marginalizable Density Models
D. Gilboa
Ari Pakman
Thibault Vatter
BDL
32
5
0
08 Jun 2021
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