Constraining effective field theories with machine learning J Brehmer, K Cranmer, G Louppe, J Pavez Physical Review Letters 121 (11), 111801, 2018 | 87 | 2018 |

Approximating likelihood ratios with calibrated discriminative classifiers K Cranmer, J Pavez, G Louppe arXiv preprint arXiv:1506.02169, 2015 | 85 | 2015 |

A guide to constraining effective field theories with machine learning J Brehmer, K Cranmer, G Louppe, J Pavez Physical Review D 98 (5), 052004, 2018 | 76 | 2018 |

Mining gold from implicit models to improve likelihood-free inference J Brehmer, G Louppe, J Pavez, K Cranmer Proceedings of the National Academy of Sciences 117 (10), 5242-5249, 2020 | 55 | 2020 |

Likelihood-free inference with an improved cross-entropy estimator M Stoye, J Brehmer, G Louppe, J Pavez, K Cranmer arXiv preprint arXiv:1808.00973, 2018 | 20 | 2018 |

Working memory networks: Augmenting memory networks with a relational reasoning module J Pavez, H Allende, H Allende-Cid arXiv preprint arXiv:1805.09354, 2018 | 17 | 2018 |

Effective LHC measurements with matrix elements and machine learning J Brehmer, K Cranmer, I Espejo, F Kling, G Louppe, J Pavez Journal of Physics: Conference Series 1525 (1), 012022, 2020 | 11 | 2020 |

Experiments using machine learning to approximate likelihood ratios for mixture models K Cranmer, J Pavez, G Louppe, WK Brooks Journal of Physics: Conference Series 762 (1), 012034, 2016 | 7 | 2016 |

carl: A likelihood-free inference toolbox G Louppe, K Cranmer, J Pavez Journal of Open Source Software 1 (1), 11, 2016 | 5 | 2016 |

Generalized matter couplings in general relativity CG Böhmer, S Carloni Physical Review D 98 (2), 024054, 2018 | 1 | 2018 |

Constraining Effective Field Theories with Machine Learning J Pavez, K Cranmer, J Brehmer, G Louppe Physical Review Letters 121 (arXiv: 1805.00013), 2018 | | 2018 |

Neural networks for the reconstruction and separation of high energy particles in a preshower calorimeter J Pavez, H Hakobyan, C Valle, W Brooks, S Kuleshov, H Allende Iberoamerican Congress on Pattern Recognition, 491-498, 2017 | | 2017 |

Approximating likelihood ratios with calibrated classifiers G Louppe, K Cranmer, J Pavez | | 2016 |

Revealing the collaborative dynamics of a large-scale arXiv text collection by means of k-shell decomposition J VERA, W PALMA, H ALLENDE, S RODRIGUEZ, J PAVEZ, E FUENTES | | |

New search J Brehmer, G Louppe, J Pavez | | |

Working Memory Networks J Pavez, H Allende, H Allende-Cid | | |