Mining gold from implicit models to improve likelihood-free inference

30 May 2018

Papers citing "Mining gold from implicit models to improve likelihood-free inference"

26 / 26 papers shown

Title
Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning Sanghwan Bae Jiwoo Hong Min Young Lee Hanbyul Kim Jeongyeon Nam Donghyun Kwak OffRL LRM 53 0 0 04 Apr 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 116 2 0 17 Jan 2025
Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods Julia Walchessen Amanda Lenzi Mikael Kuusela 35 9 0 31 Dec 2024
Full-waveform earthquake source inversion using simulation-based inference A. A. Saoulis Davide Piras A. Spurio Mancini B. Joachimi A. M. G. Ferreira 37 0 0 30 Oct 2024
FAIR Universe HiggsML Uncertainty Challenge Competition W. Bhimji P. Calafiura Ragansu Chakkappai Yuan-Tang Chou S. Diefenbacher ... D. Rousseau Benjamin Sluijter Benjamin Thorne Ihsan Ullah Yulei Zhang 34 2 0 03 Oct 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Burkner 57 3 0 23 Aug 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 31 0 0 30 Jan 2024
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests A. Coccaro Marco Letizia H. Reyes-González Riccardo Torre OOD 30 5 0 23 Feb 2023
Interpretable Uncertainty Quantification in AI for HEP Thomas Y. Chen B. Dey A. Ghosh Michael Kagan Brian D. Nord Nesar Ramachandra 30 7 0 05 Aug 2022
Neural Posterior Estimation with Differentiable Simulators Justine Zeghal F. Lanusse Alexandre Boucaud B. Remy E. Aubourg 29 14 0 12 Jul 2022
Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation C. Hahn Peter Melchior 24 28 0 14 Mar 2022
Differentiable Matrix Elements with MadJax Lukas Heinrich Michael Kagan 20 19 0 28 Feb 2022
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 33 113 0 07 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 33 31 0 25 Nov 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 31 13 0 06 Oct 2021
A Cautionary Tale of Decorrelating Theory Uncertainties A. Ghosh Benjamin Nachman 30 17 0 16 Sep 2021
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once Benjamin Nachman Jesse Thaler 27 33 0 18 Jan 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 184 0 12 Jan 2021
Towards constraining warm dark matter with stellar streams through neural simulation-based inference Joeri Hermans N. Banik Christoph Weniger G. Bertone Gilles Louppe 25 29 0 30 Nov 2020
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 24 79 0 20 Oct 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 45 117 0 10 Feb 2020
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 23 14 0 04 Jun 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 29 20 0 10 Mar 2019
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 14 47 0 12 Jun 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 43 358 0 18 May 2018
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 233 2,545 0 25 Jan 2016