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 / 1,115 papers shown
Density Estimation via Measure Transport: Outlook for Applications in the Biological Sciences
Statistical analysis and data mining (SADM), 2023
Vanessa López-Marrero
Patrick R. Johnstone
Gilchan Park
Xihaier Luo
OT
484
1
0
27 Sep 2023
Reparameterized Variational Rejection Sampling
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
M. Jankowiak
Du Phan
DRL
BDL
228
1
0
26 Sep 2023
VoiceLens: Controllable Speaker Generation and Editing with Flow
Yao Shi
Ming Li
BDL
142
1
0
25 Sep 2023
Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling
Journal of Chemical Physics (JCP), 2023
Henrik Christiansen
Federico Errica
Francesco Alesiani
204
7
0
24 Sep 2023
Testable Likelihoods for Beyond-the-Standard Model Fits
A. Beck
M. Reboud
D. van Dyk
239
1
0
19 Sep 2023
Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows
Mayeul Aubin
C. Cuesta-Lázaro
Ethan Tregidga
Javier Viana
C. Garraffo
...
R. Hargreaves
Vladimir Yu. Makhnev
J. Drake
D. Finkbeiner
P. Cargile
235
7
0
17 Sep 2023
Data-driven Modeling and Inference for Bayesian Gaussian Process ODEs via Double Normalizing Flows
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jian Xu
Shian Du
Junmei Yang
Xinghao Ding
John Paisley
Delu Zeng
216
0
0
17 Sep 2023
CppFlow: Generative Inverse Kinematics for Efficient and Robust Cartesian Path Planning
IEEE International Conference on Robotics and Automation (ICRA), 2023
Jeremy Morgan
David Millard
Gaurav Sukhatme
143
9
0
16 Sep 2023
Estimation of Counterfactual Interventions under Uncertainties
Asian Conference on Machine Learning (ACML), 2023
Juliane Weilbach
S. Gerwinn
M. Kandemir
Martin Fraenzle
203
0
0
15 Sep 2023
Differentiable JPEG: The Devil is in the Details
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Christoph Reich
Biplob K. Debnath
Deep Patel
S. Chakradhar
DiffM
307
19
0
13 Sep 2023
Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation
J. A. Raine
Samuel Klein
R. Mastandrea
Benjamin Nachman
C. Pollard
OOD
AI4CE
208
5
0
12 Sep 2023
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
International Conference on Learning Representations (ICLR), 2023
Xingchao Liu
Xiwen Zhang
Jianzhu Ma
Jian Peng
Qiang Liu
602
312
0
12 Sep 2023
Variations and Relaxations of Normalizing Flows
Keegan Kelly
Lorena Piedras
Sukrit Rao
David Samuel Roth
BDL
275
2
0
08 Sep 2023
Instructing Robots by Sketching: Learning from Demonstration via Probabilistic Diagrammatic Teaching
IEEE International Conference on Robotics and Automation (ICRA), 2023
Weiming Zhi
Tianyi Zhang
Matthew Johnson-Roberson
168
16
0
07 Sep 2023
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics
Nature Reviews Physics (Nat. Rev. Phys.), 2023
Kyle Cranmer
G. Kanwar
S. Racanière
Danilo Jimenez Rezende
P. Shanahan
AI4CE
264
34
0
03 Sep 2023
Distribution learning via neural differential equations: a nonparametric statistical perspective
Journal of machine learning research (JMLR), 2023
Youssef Marzouk
Zhi Ren
Sven Wang
Jakob Zech
226
20
0
03 Sep 2023
Diffusion Models for Interferometric Satellite Aperture Radar
A. Tuel
Thomas Kerdreux
Claudia Hulbert
B. Rouet-Leduc
230
4
0
31 Aug 2023
Computing excited states of molecules using normalizing flows
Journal of Chemical Theory and Computation (JCTC), 2023
Yahya Saleh
Álvaro Fernández Corral
Emil Vogt
Armin Iske
J. Küpper
A. Yachmenev
412
9
0
31 Aug 2023
Mixed Variational Flows for Discrete Variables
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Gian Carlo Diluvi
Benjamin Bloem-Reddy
Trevor Campbell
290
2
0
29 Aug 2023
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport
SIAM Journal of Imaging Sciences (JSIS), 2023
Zhe Xiong
Qiaoqiao Ding
Xiaoqun Zhang
OOD
302
0
0
26 Aug 2023
Learning variational autoencoders via MCMC speed measures
Statistics and computing (Stat. Comput.), 2023
Marcel Hirt
Vasileios Kreouzis
P. Dellaportas
BDL
DRL
177
2
0
26 Aug 2023
Efficient Epistemic Uncertainty Estimation in Regression Ensemble Models Using Pairwise-Distance Estimators
Lucas Berry
David Meger
UD
500
3
0
25 Aug 2023
Bayesian Exploration Networks
International Conference on Machine Learning (ICML), 2023
Matt Fellows
Brandon Kaplowitz
Christian Schroeder de Witt
Shimon Whiteson
BDL
401
4
0
24 Aug 2023
Calorimeter shower superresolution
Ian Pang
C. Pollard
David Shih
DiffM
208
12
0
22 Aug 2023
Sampling From Autoencoders' Latent Space via Quantization And Probability Mass Function Concepts
Aymene Mohammed Bouayed
Adrian Iaccovelli
D. Naccache
173
0
0
21 Aug 2023
SE(3) Equivariant Augmented Coupling Flows
Neural Information Processing Systems (NeurIPS), 2023
Laurence I. Midgley
Vincent Stimper
Javier Antorán
Emile Mathieu
Bernhard Schölkopf
José Miguel Hernández-Lobato
459
39
0
20 Aug 2023
Semi-Implicit Variational Inference via Score Matching
International Conference on Learning Representations (ICLR), 2023
Longlin Yu
Chuxu Zhang
283
19
0
19 Aug 2023
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design
AAAI Conference on Artificial Intelligence (AAAI), 2023
Ziqiao Ao
Jinglai Li
214
4
0
19 Aug 2023
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks
Neural Networks (Neural Netw.), 2023
Bangti Jin
Zehui Zhou
Jun Zou
271
4
0
18 Aug 2023
AI planning in the imagination: High-level planning on learned abstract search spaces
Carlos Martin
Tuomas Sandholm
209
0
0
16 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling
Ullrich Kothe
232
12
0
04 Aug 2023
Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimation
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Simon Dirmeier
Carlo Albert
Fernando Perez-Cruz
474
7
0
02 Aug 2023
Learning to Generate Training Datasets for Robust Semantic Segmentation
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Marwane Hariat
Olivier Laurent
Rémi Kazmierczak
Shihao Zhang
Andrei Bursuc
Angela Yao
Gianni Franchi
UQCV
313
5
0
01 Aug 2023
Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis
Conor Hassan
Roberto Salomone
Kerrie Mengersen
308
11
0
28 Jul 2023
Kernelised Normalising Flows
International Conference on Learning Representations (ICLR), 2023
Eshant English
Matthias Kirchler
Christoph Lippert
TPM
382
0
0
27 Jul 2023
Sobolev Space Regularised Pre Density Models
International Conference on Machine Learning (ICML), 2023
Mark Kozdoba
Benny Perets
Shie Mannor
197
1
0
25 Jul 2023
InVAErt networks: a data-driven framework for model synthesis and identifiability analysis
Computer Methods in Applied Mechanics and Engineering (CMAME), 2023
Guoxiang Grayson Tong
Carlos A. Sing Long
Daniele E. Schiavazzi
343
9
0
24 Jul 2023
ProtoFL: Unsupervised Federated Learning via Prototypical Distillation
IEEE International Conference on Computer Vision (ICCV), 2023
H. Kim
Youngjun Kwak
Mi-Young Jung
Jinho Shin
Youngsung Kim
Changick Kim
FedML
345
20
0
23 Jul 2023
Sig-Splines: universal approximation and convex calibration of time series generative models
Magnus Wiese
Phillip Murray
R. Korn
AI4TS
296
2
0
19 Jul 2023
Embracing the chaos: analysis and diagnosis of numerical instability in variational flows
Neural Information Processing Systems (NeurIPS), 2023
Zuheng Xu
Trevor Campbell
226
6
0
12 Jul 2023
Geometric Neural Diffusion Processes
Neural Information Processing Systems (NeurIPS), 2023
Emile Mathieu
Vincent Dutordoir
M. Hutchinson
Valentin De Bortoli
Yee Whye Teh
Richard Turner
DiffM
252
12
0
11 Jul 2023
Decorrelation using Optimal Transport
M. Algren
C. Pollard
J. A. Raine
OT
208
3
0
11 Jul 2023
LINFA: a Python library for variational inference with normalizing flow and annealing
Journal of Open Source Software (JOSS), 2023
Yu Wang
Emma R. Cobian
Jubilee Lee
Fang Liu
J. Hauenstein
Daniele E. Schiavazzi
BDL
AI4CE
287
0
0
10 Jul 2023
A generative flow for conditional sampling via optimal transport
Jason Alfonso
Ricardo Baptista
Anupam Bhakta
Noam Gal
Alfin Hou
I. Lyubimova
Daniel Pocklington
Josef Sajonz
G. Trigila
Ryan Tsai
OT
197
6
0
09 Jul 2023
Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications
Peter Tu
Zhaoyuan Yang
Leonid Sigal
Zhiwei Xu
Jing Zhang
Yiwei Fu
Dylan Campbell
Jaskirat Singh
Tianyu Wang
DiffM
555
2
0
06 Jul 2023
Performance Modeling of Data Storage Systems using Generative Models
IEEE Access (IEEE Access), 2023
A. Al-Maeeni
A. Temirkhanov
Artem Sergeevich Ryzhikov
M. Hushchyn
178
2
0
05 Jul 2023
Improved sampling via learned diffusions
International Conference on Learning Representations (ICLR), 2023
Lorenz Richter
Julius Berner
DiffM
399
87
0
03 Jul 2023
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows
M. Caselle
E. Cellini
A. Nada
232
21
0
03 Jul 2023
Transport meets Variational Inference: Controlled Monte Carlo Diffusions
International Conference on Learning Representations (ICLR), 2023
Francisco Vargas
Shreyas Padhy
Denis Blessing
Nikolas Nusken
DiffM
OT
888
13
0
03 Jul 2023
Learned harmonic mean estimation of the marginal likelihood with normalizing flows
Alicja Polanska
Matthew Alexander Price
A. Mancini
Jason D. McEwen
450
7
0
30 Jun 2023
Previous
1
2
3
...
10
11
12
...
21
22
23
Next
Page 11 of 23
Page
of 23
Go
