Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1912.02762
Cited By
v1
v2 (latest)
Normalizing Flows for Probabilistic Modeling and Inference
Journal of machine learning research (JMLR), 2019
5 December 2019
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPM
AI4CE
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Normalizing Flows for Probabilistic Modeling and Inference"
50 / 1,114 papers shown
Ab-initio study of interacting fermions at finite temperature with neural canonical transformation
Journal of Machine Learning (JML), 2021
Hao Xie
Linfeng Zhang
Lei Wang
252
30
0
18 May 2021
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows
IEEE International Conference on Robotics and Automation (ICRA), 2021
Qiangqiang Huang
Can Pu
D. Fourie
Kasra Khosoussi
Jonathan P. How
J. Leonard
153
15
0
11 May 2021
Stochastic Image-to-Video Synthesis using cINNs
Computer Vision and Pattern Recognition (CVPR), 2021
Michael Dorkenwald
Timo Milbich
A. Blattmann
Robin Rombach
Konstantinos G. Derpanis
Bjorn Ommer
DiffM
VGen
238
64
0
10 May 2021
MetaKernel: Learning Variational Random Features with Limited Labels
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Yingjun Du
Haoliang Sun
Xiantong Zhen
Jun Xu
Yilong Yin
Ling Shao
Cees G. M. Snoek
VLM
BDL
121
8
0
08 May 2021
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows
Data-Centric Engineering (DCE), 2021
Eike Cramer
Alexander Mitsos
Raúl Tempone
Manuel Dahmen
224
18
0
21 Apr 2021
Deep Data Density Estimation through Donsker-Varadhan Representation
Annals of Mathematics and Artificial Intelligence (AMAI), 2021
Seonho Park
P. Pardalos
BDL
124
7
0
14 Apr 2021
Muesli: Combining Improvements in Policy Optimization
International Conference on Machine Learning (ICML), 2021
Matteo Hessel
Ivo Danihelka
Fabio Viola
A. Guez
Simon Schmitt
Laurent Sifre
T. Weber
David Silver
H. V. Hasselt
252
67
0
13 Apr 2021
Understanding Event-Generation Networks via Uncertainties
SciPost Physics (SciPost Phys.), 2021
Marco Bellagente
Manuel Haussmann
Michel Luchmann
Tilman Plehn
BDL
215
62
0
09 Apr 2021
Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Mohsen Zand
Ali Etemad
Michael A. Greenspan
AI4CE
297
10
0
09 Apr 2021
3D Shape Generation and Completion through Point-Voxel Diffusion
IEEE International Conference on Computer Vision (ICCV), 2021
Linqi Zhou
Yilun Du
Jiajun Wu
DiffM
419
636
0
08 Apr 2021
Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
IEEE International Joint Conference on Neural Network (IJCNN), 2021
Mathias Löwe
Per Lunnemann Hansen
S. Risi
BDL
121
1
0
29 Mar 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform
Achille Thin
Yazid Janati
Sylvain Le Corff
Charles Ollion
Arnaud Doucet
Alain Durmus
Eric Moulines
C. Robert
267
7
0
17 Mar 2021
Continuous normalizing flows on manifolds
Luca Falorsi
BDL
AI4CE
159
12
0
14 Mar 2021
UnICORNN: A recurrent model for learning very long time dependencies
International Conference on Machine Learning (ICML), 2021
T. Konstantin Rusch
Siddhartha Mishra
384
73
0
09 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
720
624
0
08 Mar 2021
Combining Interventional and Observational Data Using Causal Reductions
Maximilian Ilse
Patrick Forré
Max Welling
Joris M. Mooij
OOD
CML
196
0
0
08 Mar 2021
Behavior-Driven Synthesis of Human Dynamics
Computer Vision and Pattern Recognition (CVPR), 2021
A. Blattmann
Timo Milbich
Michael Dorkenwald
Bjorn Ommer
147
16
0
08 Mar 2021
FloMo: Tractable Motion Prediction with Normalizing Flows
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021
Christoph Schöller
Alois C. Knoll
196
31
0
05 Mar 2021
Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior
SIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2021
Mario González
Andrés Almansa
Pauline Tan
326
36
0
02 Mar 2021
Posterior Meta-Replay for Continual Learning
Neural Information Processing Systems (NeurIPS), 2021
Christian Henning
Maria R. Cervera
Francesco DÁngelo
J. Oswald
Regina Traber
Benjamin Ehret
Seijin Kobayashi
Benjamin Grewe
João Sacramento
CLL
BDL
503
72
0
01 Mar 2021
Disentangling Geometric Deformation Spaces in Generative Latent Shape Models
International Journal of Computer Vision (IJCV), 2021
Tristan Aumentado-Armstrong
Stavros Tsogkas
Sven J. Dickinson
Allan D. Jepson
OCL
DRL
351
8
0
27 Feb 2021
Sparsity in long-time control of neural ODEs
C. Yagüe
Borjan Geshkovski
243
9
0
26 Feb 2021
Abelian Neural Networks
Kenshi Abe
Takanori Maehara
Issei Sato
133
2
0
24 Feb 2021
Annealed Flow Transport Monte Carlo
International Conference on Machine Learning (ICML), 2021
Michael Arbel
A. G. Matthews
Arnaud Doucet
315
94
0
15 Feb 2021
Manifold Density Estimation via Generalized Dequantization
James A. Brofos
Marcus A. Brubaker
Roy R. Lederman
265
5
0
14 Feb 2021
Jacobian Determinant of Normalizing Flows
Huadong Liao
Jiawei He
DRL
175
10
0
12 Feb 2021
Sequential Neural Posterior and Likelihood Approximation
Samuel Wiqvist
J. Frellsen
Umberto Picchini
BDL
530
38
0
12 Feb 2021
HNPE: Leveraging Global Parameters for Neural Posterior Estimation
Neural Information Processing Systems (NeurIPS), 2021
Pedro L. C. Rodrigues
Thomas Moreau
Gilles Louppe
Alexandre Gramfort
260
17
0
12 Feb 2021
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
Neural Information Processing Systems (NeurIPS), 2021
Yufeng Zhang
Wanwei Liu
Zhenbang Chen
Ji Wang
KenLi Li
478
54
0
10 Feb 2021
Automatic variational inference with cascading flows
International Conference on Machine Learning (ICML), 2021
Luca Ambrogioni
Gianluigi Silvestri
Marcel van Gerven
TPM
BDL
159
10
0
09 Feb 2021
Few-shot time series segmentation using prototype-defined infinite hidden Markov models
Yazan K. Qarout
Yordan P. Raykov
Max A. Little
AI4TS
90
0
0
07 Feb 2021
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
International Conference on Machine Learning (ICML), 2021
Kashif Rasul
Calvin Seward
Ingmar Schuster
Roland Vollgraf
DiffM
395
420
0
28 Jan 2021
Unsupervised tree boosting for learning probability distributions
Journal of machine learning research (JMLR), 2021
Naoki Awaya
Li Ma
406
7
0
26 Jan 2021
Introduction to Normalizing Flows for Lattice Field Theory
M. S. Albergo
D. Boyda
D. Hackett
G. Kanwar
Kyle Cranmer
S. Racanière
Danilo Jimenez Rezende
P. Shanahan
AI4CE
264
63
0
20 Jan 2021
MC-LSTM: Mass-Conserving LSTM
International Conference on Machine Learning (ICML), 2021
Pieter-Jan Hoedt
Frederik Kratzert
D. Klotz
Christina Halmich
Markus Holzleitner
G. Nearing
Sepp Hochreiter
Günter Klambauer
244
70
0
13 Jan 2021
Benchmarking Simulation-Based Inference
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Jan-Matthis Lueckmann
Jan Boelts
David S. Greenberg
P. J. Gonçalves
Jakob H. Macke
419
230
0
12 Jan 2021
Copula Flows for Synthetic Data Generation
Sanket Kamthe
Samuel A. Assefa
M. Deisenroth
268
65
0
03 Jan 2021
Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees
Achille Thin
Nikita Kotolevskii
Christophe Andrieu
Alain Durmus
Eric Moulines
Maxim Panov
233
5
0
31 Dec 2020
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Chris Cundy
Rishi Desai
Stefano Ermon
OffRL
430
4
0
30 Dec 2020
Score Matched Neural Exponential Families for Likelihood-Free Inference
Journal of machine learning research (JMLR), 2020
Lorenzo Pacchiardi
Ritabrata Dutta
527
29
0
20 Dec 2020
Comparison of Anomaly Detectors: Context Matters
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
V. Škvára
Jan Francå
Matěj Zorek
Tomás Pevný
Václav Smídl
351
10
0
11 Dec 2020
Full-Glow: Fully conditional Glow for more realistic image generation
German Conference on Pattern Recognition (DAGM), 2020
Moein Sorkhei
G. Henter
Hedvig Kjellström
244
7
0
10 Dec 2020
Perfect density models cannot guarantee anomaly detection
Charline Le Lan
Laurent Dinh
416
54
0
07 Dec 2020
Learning summary features of time series for likelihood free inference
Pedro L. C. Rodrigues
Alexandre Gramfort
AI4TS
102
6
0
04 Dec 2020
Universal Approximation Property of Neural Ordinary Differential Equations
Takeshi Teshima
Koichi Tojo
Masahiro Ikeda
Isao Ishikawa
Kenta Oono
214
44
0
04 Dec 2020
Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows
Neural Information Processing Systems (NeurIPS), 2020
Cheng Zhang
BDL
155
30
0
01 Dec 2020
Likelihood-Based Diverse Sampling for Trajectory Forecasting
IEEE International Conference on Computer Vision (ICCV), 2020
Yecheng Jason Ma
J. Inala
Dinesh Jayaraman
Osbert Bastani
AI4TS
267
37
0
30 Nov 2020
General Invertible Transformations for Flow-based Generative Modeling
Jakub M. Tomczak
DRL
AI4CE
179
5
0
30 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
International Conference on Learning Representations (ICLR), 2020
R. Child
BDL
VLM
442
380
0
20 Nov 2020
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
International Conference on Machine Learning (ICML), 2020
Thomas Mesnard
T. Weber
Fabio Viola
S. Thakoor
Alaa Saade
...
A. Guez
Éric Moulines
Marcus Hutter
Lars Buesing
Rémi Munos
CML
OffRL
234
67
0
18 Nov 2020
Previous
1
2
3
...
19
20
21
22
23
Next
