MadMiner: Machine learning-based inference for particle physics

24 July 2019

Papers citing "MadMiner: Machine learning-based inference for particle physics"

37 / 37 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 72 0 0 04 Apr 2025
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 151 30,069 0 01 Mar 2022
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 43 14 0 04 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 181 322 0 17 May 2019
On the Convergence of Adam and Beyond Sashank J. Reddi Satyen Kale Surinder Kumar 55 2,482 0 19 Apr 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 53 20 0 10 Mar 2019
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) Traiko Dinev Michael U. Gutmann 79 27 0 23 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 66 861 0 02 Oct 2018
Likelihood-free inference with an improved cross-entropy estimator M. Stoye Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer FedML UQCV BDL 92 48 0 02 Aug 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 212 3,110 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 232 5,024 0 19 Jun 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 104 181 0 30 May 2018
Likelihood-free inference with emulator networks Jan-Matthis Lueckmann Giacomo Bassetto Theofanis Karaletsos Jakob H. Macke 102 125 0 23 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 276 360 0 18 May 2018
A Guide to Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez 173 140 0 30 Apr 2018
Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez AI4CE 43 151 0 30 Apr 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 84 439 0 03 Apr 2018
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 110 241 0 06 Nov 2017
Adversarial Variational Optimization of Non-Differentiable Simulators Gilles Louppe Joeri Hermans Kyle Cranmer GAN 98 66 0 22 Jul 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 135 1,343 0 19 May 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 493 5,748 0 05 Dec 2016
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 134 147 0 30 Nov 2016
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 118 415 0 11 Oct 2016
WaveNet: A Generative Model for Raw Audio Aaron van den Oord Sander Dieleman Heiga Zen Karen Simonyan Oriol Vinyals Alex Graves Nal Kalchbrenner A. Senior Koray Kavukcuoglu DiffM 303 7,361 0 12 Sep 2016
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 131 2,495 0 16 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 185 3,681 0 26 May 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 104 158 0 20 May 2016
Neural Autoregressive Distribution Estimation Benigno Uria Marc-Alexandre Côté Karol Gregor Iain Murray Hugo Larochelle 70 314 0 07 May 2016
Inference Networks for Sequential Monte Carlo in Graphical Models Brooks Paige Frank Wood BDL 106 110 0 22 Feb 2016
Parameterized Machine Learning for High-Energy Physics Pierre Baldi Kyle Cranmer Taylor Faucett Peter Sadowski D. Whiteson AI4CE PINN 48 238 0 28 Jan 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 399 2,563 0 25 Jan 2016
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers Kyle Cranmer J. Pavez Gilles Louppe 77 223 0 06 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 258 4,143 0 21 May 2015
MADE: Masked Autoencoder for Distribution Estimation M. Germain Karol Gregor Iain Murray Hugo Larochelle OOD SyDa UQCV 109 863 0 12 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 850 149,474 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 96 2,251 0 30 Oct 2014
Approximate Bayesian Computation via Regression Density Estimation Yanan Fan David J. Nott Scott A. Sisson 98 62 0 06 Dec 2012