On Contrastive Learning for Likelihood-free Inference

10 February 2020

Papers citing "On Contrastive Learning for Likelihood-free Inference"

50 / 77 papers shown

Title
Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models Julius Vetter Manuel Gloeckler Daniel Gedon Jakob H Macke 36 0 0 24 Apr 2025
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biology Henrik Häggström Sebastian Persson Marija Cvijovic Umberto Picchini 24 0 0 15 Apr 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
Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference Sam Griesemer Defu Cao Zijun Cui Carolina Osorio Y. Liu 62 2 0 07 Dec 2024
Compositional simulation-based inference for time series Manuel Gloeckler S. Toyota Kenji Fukumizu Jakob H Macke 34 1 0 05 Nov 2024
Simulation-based inference with scattering representations: scattering is all you need Kiyam Lin Benjamin Joachimi Jason D. McEwen 21 1 0 11 Oct 2024
Cost-aware Simulation-based Inference Ayush Bharti Daolang Huang Samuel Kaski F. Briol 28 1 0 10 Oct 2024
A Comprehensive Guide to Simulation-based Inference in Computational Biology Xiaoyu Wang Ryan P. Kelly A. Jenner D. Warne Christopher C. Drovandi 28 3 0 29 Sep 2024
Embed and Emulate: Contrastive representations for simulation-based inference Ruoxi Jiang Peter Y. Lu Rebecca Willett 24 0 0 27 Sep 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 35 0 0 22 Jul 2024
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 35 6 0 05 Jun 2024
On the Sequence Evaluation based on Stochastic Processes Tianhao Zhang Zhexiao Lin Zhecheng Sheng Chen Jiang Dongyeop Kang 27 0 0 28 May 2024
Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs Sanmitra Ghosh Paul J. Birrell Daniela De Angelis 43 1 0 02 May 2024
All-in-one simulation-based inference Manuel Gloeckler Michael Deistler Christian Weilbach Frank D. Wood Jakob H. Macke 29 26 0 15 Apr 2024
Simulation-Based Inference with Quantile Regression He Jia 15 2 0 04 Jan 2024
Consistency Models for Scalable and Fast Simulation-Based Inference Marvin Schmitt Valentin Pratz Ullrich Kothe Paul-Christian Burkner Stefan T. Radev 16 9 0 09 Dec 2023
Pseudo-Likelihood Inference Theo Gruner Boris Belousov Fabio Muratore Daniel Palenicek Jan Peters 21 0 0 28 Nov 2023
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability Maciej Falkiewicz Naoya Takeishi Imahn Shekhzadeh Antoine Wehenkel Arnaud Delaunoy Gilles Louppe Alexandros Kalousis 19 6 0 20 Oct 2023
Simulation-based inference using surjective sequential neural likelihood estimation Simon Dirmeier Carlo Albert F. Pérez-Cruz 13 6 0 02 Aug 2023
Binary classification based Monte Carlo simulation Elouan Argouarc'h F. Desbouvries 10 0 0 29 Jul 2023
Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference Vincent D. Zaballa E. Hui 12 2 0 27 Jun 2023
Adaptive Conditional Quantile Neural Processes Peiman Mohseni N. Duffield Bani Mallick Arman Hasanzadeh 22 3 0 30 May 2023
Flow Matching for Scalable Simulation-Based Inference Maximilian Dax J. Wildberger Simon Buchholz Stephen R. Green Jakob H. Macke Bernhard Schölkopf 13 48 0 26 May 2023
Learning Robust Statistics for Simulation-based Inference under Model Misspecification Daolang Huang Ayush Bharti Amauri Souza Luigi Acerbi Samuel Kaski 38 30 0 25 May 2023
Reliable Gradient-free and Likelihood-free Prompt Tuning Maohao Shen S. Ghosh P. Sattigeri Subhro Das Yuheng Bu G. Wornell VLM 44 10 0 30 Apr 2023
Balancing Simulation-based Inference for Conservative Posteriors Arnaud Delaunoy Benjamin Kurt Miller Patrick Forré Christoph Weniger Gilles Louppe 33 9 0 21 Apr 2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models Stefan T. Radev Marvin Schmitt Valentin Pratz Umberto Picchini Ullrich Kothe Paul-Christian Burkner BDL 17 29 0 17 Feb 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
Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning Aurelio Amerio A. Cuoco N. Fornengo 19 4 0 03 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 20 10 0 31 Jan 2023
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation O. Chehab Alexandre Gramfort Aapo Hyvarinen SSL 22 3 0 23 Jan 2023
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy Michael J. Smith James E. Geach 16 32 0 07 Nov 2022
From Denoising Diffusions to Denoising Markov Models Joe Benton Yuyang Shi Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 66 25 0 07 Nov 2022
Robust Neural Posterior Estimation and Statistical Model Criticism Daniel Ward Patrick W Cannon Mark Beaumont Matteo Fasiolo Sebastian M. Schmon 14 36 0 12 Oct 2022
Contrastive Neural Ratio Estimation for Simulation-based Inference Benjamin Kurt Miller Christoph Weniger Patrick Forré 6 15 0 11 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 48 33 0 10 Oct 2022
Truncated proposals for scalable and hassle-free simulation-based inference Michael Deistler P. J. Gonçalves Jakob H Macke 11 48 0 10 Oct 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 6 34 0 05 Sep 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy Joeri Hermans François Rozet Antoine Wehenkel Gilles Louppe 13 30 0 29 Aug 2022
Adversarial Bayesian Simulation YueXing Wang Veronika Rovcková GAN BDL 19 5 0 25 Aug 2022
Neural Posterior Estimation with Differentiable Simulators Justine Zeghal F. Lanusse Alexandre Boucaud B. Remy E. Aubourg 13 14 0 12 Jul 2022
Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation Ye Zhu Yuehua Wu Kyle Olszewski Jian Ren Sergey Tulyakov Yan Yan DiffM 20 47 0 15 Jun 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
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 11 7 0 29 Apr 2022
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 26 33 0 12 Mar 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 16 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
Black-box Bayesian inference for economic agent-based models Joel Dyer Patrick W Cannon J. Farmer Sebastian M. Schmon 11 23 0 01 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