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1711.01861
Cited By
Flexible statistical inference for mechanistic models of neural dynamics
6 November 2017
Jan-Matthis Lueckmann
P. J. Gonçalves
Giacomo Bassetto
Kaan Öcal
M. Nonnenmacher
Jakob H. Macke
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Papers citing
"Flexible statistical inference for mechanistic models of neural dynamics"
29 / 29 papers shown
Title
Robust Simulation-Based Inference under Missing Data via Neural Processes
Yogesh Verma
Ayush Bharti
Vikas K. Garg
63
0
0
03 Mar 2025
Multifidelity Simulation-based Inference for Computationally Expensive Simulators
Anastasia N. Krouglova
Hayden R. Johnson
Basile Confavreux
Michael Deistler
P. J. Gonçalves
71
1
0
17 Feb 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation
Yifei Xiong
Xiliang Yang
Sanguo Zhang
Zhijian He
108
2
0
17 Jan 2025
Compositional simulation-based inference for time series
Manuel Gloeckler
S. Toyota
Kenji Fukumizu
Jakob H Macke
37
1
0
05 Nov 2024
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Paul E. Chang
Nasrulloh Loka
Daolang Huang
Ulpu Remes
Samuel Kaski
Luigi Acerbi
AI4CE
41
4
0
20 Oct 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods
Xiliang Yang
Yifei Xiong
Zhijian He
16
0
0
30 Jan 2024
Amortized Bayesian Decision Making for simulation-based models
Mila Gorecki
Jakob H. Macke
Michael Deistler
18
1
0
05 Dec 2023
Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers
Guy Moss
V. Višnjević
Olaf Eisen
Falk M. Oraschewski
Cornelius Schroder
Jakob H. Macke
R. Drews
6
1
0
03 Dec 2023
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
27
72
0
21 May 2023
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
Pablo Lemos
A. Coogan
Y. Hezaveh
Laurence Perreault Levasseur
27
30
0
06 Feb 2023
Compositional Score Modeling for Simulation-based Inference
Tomas Geffner
George Papamakarios
A. Mnih
60
24
0
28 Sep 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
Arnaud Delaunoy
Joeri Hermans
François Rozet
Antoine Wehenkel
Gilles Louppe
24
30
0
29 Aug 2022
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization
Lorenzo Pacchiardi
Ritabrata Dutta
TPM
BDL
UQCV
GAN
13
18
0
31 May 2022
Variational methods for simulation-based inference
Manuel Glöckler
Michael Deistler
Jakob H. Macke
19
46
0
08 Mar 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation
Joel Dyer
Patrick W Cannon
Sebastian M. Schmon
16
9
0
23 Feb 2022
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks
Marvin Schmitt
Paul-Christian Burkner
Ullrich Kothe
Stefan T. Radev
22
34
0
16 Dec 2021
Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes
D. Warne
Thomas P. Prescott
Ruth Baker
Matthew J. Simpson
16
15
0
26 Oct 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond
Dinghuai Zhang
Jie Fu
Yoshua Bengio
Aaron Courville
29
13
0
06 Oct 2021
Simulation-based Bayesian inference for multi-fingered robotic grasping
Norman Marlier
O. Bruls
Gilles Louppe
24
6
0
29 Sep 2021
Real-time gravitational-wave science with neural posterior estimation
Maximilian Dax
Stephen R. Green
J. Gair
Jakob H. Macke
A. Buonanno
Bernhard Schölkopf
13
130
0
23 Jun 2021
Fitting summary statistics of neural data with a differentiable spiking network simulator
G. Bellec
Shuqi Wang
Alireza Modirshanechi
Johanni Brea
W. Gerstner
26
11
0
18 Jun 2021
Sequential Neural Posterior and Likelihood Approximation
Samuel Wiqvist
J. Frellsen
Umberto Picchini
BDL
26
33
0
12 Feb 2021
Likelihood-Free Inference with Deep Gaussian Processes
Alexander Aushev
Henri Pesonen
Markus Heinonen
J. Corander
Samuel Kaski
GP
18
10
0
18 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods
Luigi Acerbi
17
40
0
15 Jun 2020
On Contrastive Learning for Likelihood-free Inference
Conor Durkan
Iain Murray
George Papamakarios
BDL
34
117
0
10 Feb 2020
Inference of a mesoscopic population model from population spike trains
M. Slawski
A. Longtin
E. Ben-David
11
12
0
03 Oct 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows
George Papamakarios
D. Sterratt
Iain Murray
BDL
33
358
0
18 May 2018
ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations
Rafael Izbicki
Ann B. Lee
T. Pospisil
16
34
0
14 May 2018
Bayesian latent structure discovery from multi-neuron recordings
Scott W. Linderman
Ryan P. Adams
Jonathan W. Pillow
9
54
0
26 Oct 2016
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