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1910.13233
Cited By
Neural Density Estimation and Likelihood-free Inference
29 October 2019
George Papamakarios
BDL
DRL
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Papers citing
"Neural Density Estimation and Likelihood-free Inference"
14 / 14 papers shown
Title
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Aastha Acharya
Caleb Lee
Marissa DÁlonzo
Jared Shamwell
Nisar R. Ahmed
Rebecca L. Russell
BDL
46
0
0
30 May 2024
Unifying Simulation and Inference with Normalizing Flows
Haoxing Du
Claudius Krause
Vinicius Mikuni
Benjamin Nachman
Ian Pang
David Shih
42
3
0
29 Apr 2024
Universal Approximation and the Topological Neural Network
M. Kouritzin
Daniel Richard
21
0
0
26 May 2023
Machine-Learned Exclusion Limits without Binning
E. Arganda
Andrés D. Pérez
M. D. L. Rios
Rosa María Sandá Seoane
30
9
0
09 Nov 2022
m
∗
m^\ast
m
∗
of two-dimensional electron gas: a neural canonical transformation study
H.-j. Xie
Linfeng Zhang
Lei Wang
28
8
0
10 Jan 2022
Feature Alignment as a Generative Process
T. S. Farias
Jonas Maziero
DiffM
BDL
18
1
0
23 Jun 2021
Solving Schrödinger Bridges via Maximum Likelihood
Francisco Vargas
Pierre Thodoroff
Neil D. Lawrence
A. Lamacraft
OT
26
131
0
03 Jun 2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation
Chris Waites
Rachel Cummings
19
15
0
25 Mar 2021
On Contrastive Learning for Likelihood-free Inference
Conor Durkan
Iain Murray
George Papamakarios
BDL
45
117
0
10 Feb 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
282
10,354
0
12 Dec 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
284
2,890
0
15 Sep 2016
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
A. Gretton
BDL
107
324
0
09 Feb 2016
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
242
2,550
0
25 Jan 2016
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,266
0
09 Jun 2012
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