| The machine learning landscape of top taggers G Kasieczka, T Plehn, A Butter, K Cranmer, D Debnath, BM Dillon, ... SciPost Physics 7 (1), 014, 2019 | 226 | 2019 |
| Pulling out all the tops with computer vision and deep learning S Macaluso, D Shih Journal of High Energy Physics 2018 (10), 1-27, 2018 | 173 | 2018 |
| Revealing compressed stops using high-momentum recoils S Macaluso, M Park, D Shih, B Tweedie Journal of High Energy Physics 2016 (3), 1-16, 2016 | 71 | 2016 |
| Cornering natural SUSY at LHC Run II and beyond MR Buckley, D Feld, S Macaluso, A Monteux, D Shih Journal of High Energy Physics 2017 (8), 1-34, 2017 | 58 | 2017 |
| Deep inelastic scattering from holographic spin-one hadrons E Koile, S Macaluso, M Schvellinger Journal of High Energy Physics 2012 (2), 1-37, 2012 | 20 | 2012 |
| Deep inelastic scattering structure functions of holographic spin-1 hadrons with N f≥ 1 E Koile, S Macaluso, M Schvellinger Journal of High Energy Physics 2014 (1), 1-41, 2014 | 19 | 2014 |
| Reframing jet physics with new computational methods K Cranmer, M Drnevich, S Macaluso, D Pappadopulo EPJ Web of Conferences 251, 03059, 2021 | 12 | 2021 |
| Dark matter and the Higgs in natural SUSY A Basirnia, S Macaluso, D Shih Journal of High Energy Physics 2017 (3), 1-32, 2017 | 12 | 2017 |
| Hierarchical clustering in particle physics through reinforcement learning J Brehmer, S Macaluso, D Pappadopulo, K Cranmer arXiv preprint arXiv:2011.08191, 2020 | 6 | 2020 |
| Compact Representation of Uncertainty in Hierarchical Clustering CS Greenberg, S Macaluso, N Monath, JA Lee, P Flaherty, K Cranmer, ... arXiv preprint arXiv:2002.11661, 1-21, 2020 | 5 | 2020 |
| Toy Generative Model for Jets Package K Cranmer, S Macaluso, D Pappadopulo | 5 | 2019 |
| Toy Generative Model for Jets, 2019 K Cranmer, S Macaluso, D Pappadopulo URL https://github. com/SebastianMacaluso/ToyJetsShower/blob/master/notes …, 2019 | 5 | 2019 |
| Toy Generative Model for Jets Package (2019) K Cranmer, S Macaluso, D Pappadopulo | 5 | |
| Exact and approximate hierarchical clustering using A CS Greenberg, S Macaluso, N Monath, A Dubey, P Flaherty, M Zaheer, ... Uncertainty in Artificial Intelligence, 2061-2071, 2021 | 4 | 2021 |
| Toy Generative Model for Jets K Cranmer, S Macaluso, D Pappadopulo Toy Generative Model for Jets, 2019 | 4 | 2019 |
| The Quantum Trellis: A classical algorithm for sampling the parton shower with interference effects S Macaluso, K Cranmer arXiv preprint arXiv:2112.12795, 2021 | 3 | 2021 |
| Cluster trellis: Data structures & algorithms for exact inference in hierarchical clustering S Macaluso, C Greenberg, N Monath, JA Lee, P Flaherty, K Cranmer, ... International Conference on Artificial Intelligence and Statistics, 2467-2475, 2021 | 3 | 2021 |
| Cluster trellis: Data structures & algorithms for exact inference in hierarchical clustering C Greenberg, S Macaluso, N Monath, JA Lee, P Flaherty, K Cranmer, ... AISTATS, 2021 | 2 | 2021 |
| Data Structures & Algorithms for Exact Inference in Hierarchical Clustering CS Greenberg, S Macaluso, N Monath, JA Lee, P Flaherty, K Cranmer, ... arXiv preprint arXiv:2002.11661, 2020 | 2 | 2020 |
| The Machine Learning Landscape of Top Taggers M Fairbairn, DA Faroughy, W Fedorko, C Gay, L Gouskos, JF Kamenik, ... arXiv preprint arXiv:1902.09914, 2019 | | 2019 |
