| Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors CN Coelho, A Kuusela, S Li, H Zhuang, J Ngadiuba, TK Aarrestad, ... Nature Machine Intelligence 3 (8), 675-686, 2021 | 193* | 2021 |
| Anomaly detection with conditional variational autoencoders AA Pol, V Berger, C Germain, G Cerminara, M Pierini 2019 18th IEEE international conference on machine learning and applications …, 2019 | 133 | 2019 |
| hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices F Fahim, B Hawks, C Herwig, J Hirschauer, S Jindariani, N Tran, ... arXiv preprint arXiv:2103.05579, 2021 | 113 | 2021 |
| Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider E Govorkova, E Puljak, T Aarrestad, T James, V Loncar, M Pierini, AA Pol, ... Nature Machine Intelligence 4 (2), 154-161, 2022 | 57 | 2022 |
| Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron Collider AA Pol, G Cerminara, C Germain, M Pierini, A Seth Computing and Software for Big Science 3, 1-13, 2019 | 32 | 2019 |
| Deep learning for certification of the quality of the data acquired by the CMS Experiment AA Pol, V Azzolini, G Cerminara, F De Guio, G Franzoni, C Germain, ... Journal of Physics: Conference Series 1525 (1), 012045, 2020 | 20* | 2020 |
| Monte Carlo production management at CMS G Boudoul, G Franzoni, A Norkus, A Pol, P Srimanobhas, JR Vlimant Journal of Physics: Conference Series 664 (7), 072018, 2015 | 15 | 2015 |
| Improving data quality monitoring via a partnership of technologies and resources between the CMS experiment at CERN and industry V Azzolin, M Andrews, G Cerminara, N Dev, C Jessop, N Marinelli, ... EPJ Web of Conferences 214, 01007, 2019 | 13 | 2019 |
| Fit: A metric for model sensitivity B Zandonati, AA Pol, M Pierini, O Sirkin, T Kopetz arXiv preprint arXiv:2210.08502, 2022 | 6 | 2022 |
| Data quality monitoring anomaly detection AA Pol, G Cerminara, C Germain, M Pierini Artificial Intelligence for High Energy Physics, 115-149, 2022 | 6 | 2022 |
| Machine learning anomaly detection applications to compact muon solenoid data quality monitoring AA Pol Université Paris-Saclay, 2020 | 5 | 2020 |
| Symbolic regression on FPGAs for fast machine learning inference HF Tsoi, AA Pol, V Loncar, E Govorkova, M Cranmer, S Dasu, P Elmer, ... arXiv preprint arXiv:2305.04099, 2023 | 3 | 2023 |
| Lightweight jet reconstruction and identification as an object detection task AA Pol, T Aarrestad, E Govorkova, R Halily, A Klempner, T Kopetz, ... Machine Learning: Science and Technology 3 (2), 025016, 2022 | 3* | 2022 |
| Deep learning for inferring cause of data anomalies V Azzolini, M Borisyak, G Cerminara, D Derkach, G Franzoni, F De Guio, ... Journal of Physics: Conference Series 1085 (4), 042015, 2018 | 2 | 2018 |
| Knowledge Distillation for Anomaly Detection AA Pol, E Govorkova, S Gronroos, N Chernyavskaya, P Harris, M Pierini, ... arXiv preprint arXiv:2310.06047, 2023 | | 2023 |
| Towards Optimal Compression: Joint Pruning and Quantization B Zandonati, G Bucagu, AA Pol, M Pierini, O Sirkin, T Kopetz arXiv preprint arXiv:2302.07612, 2023 | | 2023 |
| HL-LHC Computing Review: Common Tools and Community Software HEP Foundation, T Aarrestad, S Amoroso, MJ Atkinson, J Bendavid, ... arXiv preprint arXiv:2008.13636, 2020 | | 2020 |
| Monitoring of the data processing and simulated production at CMS with a web-based service: the Production Monitoring Platform (pMp) G Franzoni, A Norkus, AA Pol, N Srimanobhas, J Walker Journal of Physics: Conference Series 898 (9), 092038, 2017 | | 2017 |
