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Novel and flexible parameter estimation methods for data-consistent
  inversion in mechanistic modeling

Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modeling

17 September 2020
Timothy Rumbell
Jaimit Parikh
J. Kozloski
V. Gurev
ArXivPDFHTML

Papers citing "Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modeling"

25 / 25 papers shown
Title
GATSBI: Generative Adversarial Training for Simulation-Based Inference
GATSBI: Generative Adversarial Training for Simulation-Based Inference
Poornima Ramesh
Jan-Matthis Lueckmann
Jan Boelts
Álvaro Tejero-Cantero
David S. Greenberg
P. J. Gonçalves
Jakob H. Macke
GAN
68
37
0
12 Mar 2022
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
270
30,123
0
01 Mar 2022
Benchmarking Simulation-Based Inference
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann
Jan Boelts
David S. Greenberg
P. J. Gonçalves
Jakob H. Macke
254
195
0
12 Jan 2021
Learning Quantities of Interest from Dynamical Systems for
  Observation-Consistent Inversion
Learning Quantities of Interest from Dynamical Systems for Observation-Consistent Inversion
S. Mattis
Kyle R. Steffen
T. Butler
C. Dawson
D. Estep
11
6
0
15 Sep 2020
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of
  Generative Models
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
Sachit Menon
Alexandru Damian
Shijia Hu
Nikhil Ravi
Cynthia Rudin
OOD
DiffM
240
551
0
08 Mar 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows
  and Latent Variable Models
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models
Chin-Wei Huang
Laurent Dinh
Aaron Courville
DRL
64
89
0
17 Feb 2020
Normalizing Flows for Probabilistic Modeling and Inference
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPM
AI4CE
202
1,691
0
05 Dec 2019
The frontier of simulation-based inference
The frontier of simulation-based inference
Kyle Cranmer
Johann Brehmer
Gilles Louppe
AI4CE
172
851
0
04 Nov 2019
Stabilizing Generative Adversarial Networks: A Survey
Stabilizing Generative Adversarial Networks: A Survey
Maciej Wiatrak
Stefano V. Albrecht
A. Nystrom
GAN
60
86
0
30 Sep 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
406
5,103
0
19 Jun 2018
Likelihood-free inference with emulator networks
Likelihood-free inference with emulator networks
Jan-Matthis Lueckmann
Giacomo Bassetto
Theofanis Karaletsos
Jakob H. Macke
161
128
0
23 May 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Henry Gouk
E. Frank
Bernhard Pfahringer
M. Cree
170
477
0
12 Apr 2018
Boosted Density Estimation Remastered
Boosted Density Estimation Remastered
Zac Cranko
Richard Nock
GAN
30
12
0
22 Mar 2018
Spectral Normalization for Generative Adversarial Networks
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato
Toshiki Kataoka
Masanori Koyama
Yuichi Yoshida
ODL
155
4,437
0
16 Feb 2018
Pros and Cons of GAN Evaluation Measures
Pros and Cons of GAN Evaluation Measures
Ali Borji
ELM
EGVM
65
874
0
09 Feb 2018
Easy High-Dimensional Likelihood-Free Inference
Easy High-Dimensional Likelihood-Free Inference
Vinay Jethava
Devdatt Dubhashi
BDL
GAN
254
3
0
29 Nov 2017
Adversarial Variational Optimization of Non-Differentiable Simulators
Adversarial Variational Optimization of Non-Differentiable Simulators
Gilles Louppe
Joeri Hermans
Kyle Cranmer
GAN
151
66
0
22 Jul 2017
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational
  Learning
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava
Lazar Valkov
Chris Russell
Michael U. Gutmann
Charles Sutton
SyDa
GAN
60
678
0
22 May 2017
Variational Inference using Implicit Distributions
Variational Inference using Implicit Distributions
Ferenc Huszár
DRL
GAN
158
135
0
27 Feb 2017
Photo-Realistic Single Image Super-Resolution Using a Generative
  Adversarial Network
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
C. Ledig
Lucas Theis
Ferenc Huszár
Jose Caballero
Andrew Cunningham
...
Andrew P. Aitken
Alykhan Tejani
J. Totz
Zehan Wang
Wenzhe Shi
GAN
242
10,686
0
15 Sep 2016
Improving Variational Inference with Inverse Autoregressive Flow
Improving Variational Inference with Inverse Autoregressive Flow
Diederik P. Kingma
Tim Salimans
Rafal Jozefowicz
Xi Chen
Ilya Sutskever
Max Welling
BDL
DRL
135
1,818
0
15 Jun 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence
  Minimization
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
GAN
149
1,655
0
02 Jun 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
Conditional Generative Adversarial Nets
Conditional Generative Adversarial Nets
M. Berk Mirza
Simon Osindero
GAN
SyDa
AI4CE
258
10,409
0
06 Nov 2014
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian
  Monte Carlo
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman
Andrew Gelman
165
4,300
0
18 Nov 2011
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