Weakly Supervised Classification in High Energy Physics

1 February 2017

Papers citing "Weakly Supervised Classification in High Energy Physics"

31 / 31 papers shown

Title
Nearly Optimal Sample Complexity for Learning with Label Proportions R. Busa-Fekete Travis Dick Claudio Gentile Haim Kaplan Tomer Koren Uri Stemmer 53 0 0 08 May 2025
Strengthening Anomaly Awareness Adam Banda Charanjit K. Khosa V. Sanz 37 0 0 15 Apr 2025
Optimal Equivariant Architectures from the Symmetries of Matrix-Element Likelihoods Daniel Maître Vishal S. Ngairangbam M. Spannowsky 42 4 0 24 Oct 2024
Optimistic Rates for Learning from Label Proportions Gene Li Lin Chen Adel Javanmard Vahab Mirrokni 43 2 0 01 Jun 2024
FRACTAL: Fine-Grained Scoring from Aggregate Text Labels Yukti Makhija Priyanka Agrawal Rishi Saket A. Raghuveer 37 0 0 07 Apr 2024
Hardness of Learning Boolean Functions from Label Proportions V. Guruswami Rishi Saket 19 0 0 28 Mar 2024
Machine Learning for Anomaly Detection in Particle Physics Vasilis Belis Patrick Odagiu Thea Klæboe Årrestad 35 40 0 20 Dec 2023
PAC Learning Linear Thresholds from Label Proportions Anand Brahmbhatt Rishi Saket A. Raghuveer 44 5 0 16 Oct 2023
LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions Anand Brahmbhatt Mohith Pokala Rishi Saket A. Raghuveer 25 3 0 16 Oct 2023
Label Differential Privacy via Aggregation Anand Brahmbhatt Rishi Saket Shreyas Havaldar Anshul Nasery A. Raghuveer 45 0 0 16 Oct 2023
Easy Learning from Label Proportions R. Busa-Fekete Heejin Choi Travis Dick Claudio Gentile Andrés Munoz Medina 17 13 0 06 Feb 2023
The Tensor Data Platform: Towards an AI-centric Database System Apurva Gandhi Yuki Asada Victor Fu Advitya Gemawat Lihao Zhang Rathijit Sen Carlo Curino Jesús Camacho-Rodríguez Matteo Interlandi 21 14 0 04 Nov 2022
Learning from Label Proportions with Instance-wise Consistency Ryoma Kobayashi Yusuke Mukuta Tatsuya Harada 33 2 0 24 Mar 2022
Learning from Label Proportions by Learning with Label Noise Jianxin Zhang Yutong Wang Clayton Scott NoLa 27 24 0 04 Mar 2022
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 49 113 0 07 Dec 2021
Challenges for Unsupervised Anomaly Detection in Particle Physics Katherine Fraser S. Homiller Rashmish K. Mishra B. Ostdiek M. Schwartz DRL 34 43 0 13 Oct 2021
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider T. Aarrestad M. Beekveld M. Bona A. Boveia S. Caron ... M. White E. Wulff E. Wallin K. Wozniak Z. Zhang 21 81 0 28 May 2021
Autoencoders for unsupervised anomaly detection in high energy physics Thorben Finke Michael Krämer A. Morandini A. Mück I. Oleksiyuk 31 83 0 19 Apr 2021
A Living Review of Machine Learning for Particle Physics Matthew Feickert Benjamin Nachman KELM AI4CE 39 178 0 02 Feb 2021
Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review T. Dorigo P. D. Castro 16 14 0 17 Jul 2020
Learning from Label Proportions: A Mutual Contamination Framework Clayton Scott Jianxin Zhang SSL 17 13 0 12 Jun 2020
Class Imbalance Techniques for High Energy Physics C. Murphy 20 7 0 01 May 2019
Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra A. Chakraborty Sung Hak Lim M. Nojiri 42 43 0 03 Apr 2019
Energy Flow Networks: Deep Sets for Particle Jets Patrick T. Komiske E. Metodiev Jesse Thaler PINN 3DPC 36 251 0 11 Oct 2018
Deep Learning from Label Proportions for Emphysema Quantification Gerda Bortsova Florian Dubost S. Ørting Ioannis Katramados Laurens Hogeweg L. Thomsen M. Wille Marleen de Bruijne 19 30 0 23 Jul 2018
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 24 47 0 12 Jun 2018
On the Topic of Jets: Disentangling Quarks and Gluons at Colliders E. Metodiev Jesse Thaler 23 71 0 31 Jan 2018
Learning to Classify from Impure Samples with High-Dimensional Data Patrick T. Komiske E. Metodiev Benjamin Nachman M. Schwartz 19 76 0 30 Jan 2018
Classification without labels: Learning from mixed samples in high energy physics E. Metodiev Benjamin Nachman Jesse Thaler CML 13 205 0 09 Aug 2017
Pileup Mitigation with Machine Learning (PUMML) Patrick T. Komiske E. Metodiev Benjamin Nachman M. Schwartz 18 99 0 26 Jul 2017
(Machine) Learning to Do More with Less T. Cohen M. Freytsis B. Ostdiek 11 81 0 28 Jun 2017