Flexible statistical inference for mechanistic models of neural dynamics

6 November 2017

Jan-Matthis Lueckmann

Jakob H. Macke

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