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"

20 / 20 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 48 3 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 108 2 0 17 Jan 2025
Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods Julia Walchessen Amanda Lenzi Mikael Kuusela 30 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 35 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 27 1 0 03 Oct 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Burkner 50 3 0 23 Aug 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 16 0 0 30 Jan 2024
Interpretable Uncertainty Quantification in AI for HEP Thomas Y. Chen B. Dey A. Ghosh Michael Kagan Brian D. Nord Nesar Ramachandra 19 7 0 05 Aug 2022
Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation C. Hahn Peter Melchior 11 28 0 14 Mar 2022
Differentiable Matrix Elements with MadJax Lukas Heinrich Michael Kagan 12 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 26 113 0 07 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 31 31 0 25 Nov 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
A Cautionary Tale of Decorrelating Theory Uncertainties A. Ghosh Benjamin Nachman 15 17 0 16 Sep 2021
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once Benjamin Nachman Jesse Thaler 16 33 0 18 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
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 34 117 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 12 14 0 04 Jun 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 33 358 0 18 May 2018
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 225 2,543 0 25 Jan 2016