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Maurizio Pierini
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2020 – today
- 2024
- [j24]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Dongning Guo, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo
, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Shen Wang, Thomas K. Warburton:
Corrigendum: Applications and techniques for fast machine learning in science. Frontiers Big Data 6 (2024) - [j23]Patrick Odagiu
Ultrafast jet classification at the HL-LHC. Mach. Learn. Sci. Technol. 5(3): 35017 (2024) - [j22]Luca Anzalone
Triggering dark showers with conditional dual auto-encoders. Mach. Learn. Sci. Technol. 5(3): 35064 (2024) - [j21]Zhiqiang Que
LL-GNN: Low Latency Graph Neural Networks on FPGAs for High Energy Physics. ACM Trans. Embed. Comput. Syst. 23(2): 17:1-17:28 (2024) - [i49]Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad:
Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. CoRR abs/2402.01876 (2024) - 2023
- [j20]Sonja Grönroos
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier. Mach. Learn. Sci. Technol. 4(3): 35028 (2023) - [j19]Breno Orzari
LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows. Mach. Learn. Sci. Technol. 4(4): 45023 (2023) - [j18]Julian Schuhmacher
Unravelling physics beyond the standard model with classical and quantum anomaly detection. Mach. Learn. Sci. Technol. 4(4): 45031 (2023) - [j17]Rohan Shenoy
Differentiable Earth mover's distance for data compression at the high-luminosity LHC. Mach. Learn. Sci. Technol. 4(4): 45058 (2023) - [c7]Adrian Alan Pol, Ekaterina Govorkova, Sonja Grönroos, Nadezda Chernyavskaya, Philip C. Harris, Maurizio Pierini, Isobel Ojalvo, Peter Elmer:
Knowledge Distillation for Anomaly Detection. ESANN 2023 - [c6]Ben Zandonati, Adrian Alan Pol, Maurizio Pierini, Olya Sirkin, Tal Kopetz:
FIT: A Metric for Model Sensitivity. ICLR 2023 - [i48]Kinga Anna Wozniak, Vasilis Belis, Ema Puljak, Panagiotis Kl. Barkoutsos, Günther Dissertori, Michele Grossi
Quantum anomaly detection in the latent space of proton collision events at the LHC. CoRR abs/2301.10780 (2023) - [i47]Julian Schuhmacher, Laura Boggia, Vasilis Belis, Ema Puljak, Michele Grossi
Unravelling physics beyond the standard model with classical and quantum anomaly detection. CoRR abs/2301.10787 (2023) - [i46]Ben Zandonati, Glenn Bucagu, Adrian Alan Pol, Maurizio Pierini, Olya Sirkin, Tal Kopetz:
Towards Optimal Compression: Joint Pruning and Quantization. CoRR abs/2302.07612 (2023) - [i45]Sonja Grönroos, Maurizio Pierini, Nadezda Chernyavskaya:
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier. CoRR abs/2303.15319 (2023) - [i44]Farouk Mokhtar, Joosep Pata, Javier M. Duarte, Eric Wulff, Maurizio Pierini, Jean-Roch Vlimant:
Progress towards an improved particle flow algorithm at CMS with machine learning. CoRR abs/2303.17657 (2023) - [i43]Ho Fung Tsoi, Adrian Alan Pol, Vladimir Loncar, Ekaterina Govorkova, Miles D. Cranmer
Symbolic Regression on FPGAs for Fast Machine Learning Inference. CoRR abs/2305.04099 (2023) - [i42]Rohan Shenoy, Javier M. Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez:
Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC. CoRR abs/2306.04712 (2023) - [i41]Luca Anzalone, Simranjit Singh Chhibra, Benedikt Maier
Triggering Dark Showers with Conditional Dual Auto-Encoders. CoRR abs/2306.12955 (2023) - [i40]Simranjit Singh Chhibra, Nadezda Chernyavskaya, Benedikt Maier, Maurizio Pierini, Syed Hasan:
Autoencoders for Real-Time SUEP Detection. CoRR abs/2306.13595 (2023) - [i39]Adrian Alan Pol, Ekaterina Govorkova, Sonja Grönroos, Nadezda Chernyavskaya, Philip C. Harris, Maurizio Pierini, Isobel Ojalvo, Peter Elmer:
Knowledge Distillation for Anomaly Detection. CoRR abs/2310.06047 (2023) - 2022
- [j16]Allison McCarn Deiana, Nhan Tran
Applications and Techniques for Fast Machine Learning in Science. Frontiers Big Data 5: 787421 (2022) - [j15]Pratik Jawahar
Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows. Frontiers Big Data 5: 803685 (2022) - [j14]Eric A. Moreno
Source-agnostic gravitational-wave detection with recurrent autoencoders. Mach. Learn. Sci. Technol. 3(2): 25001 (2022) - [j13]Adrian Alan Pol
Lightweight jet reconstruction and identification as an object detection task. Mach. Learn. Sci. Technol. 3(2): 25016 (2022) - [j12]Mary Touranakou
Particle-based fast jet simulation at the LHC with variational autoencoders. Mach. Learn. Sci. Technol. 3(3): 35003 (2022) - [j11]Nicolò Ghielmetti
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. Mach. Learn. Sci. Technol. 3(4): 45011 (2022) - [j10]Ekaterina Govorkova
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nat. Mach. Intell. 4(2): 154-161 (2022) - [j9]Ekaterina Govorkova
Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. Nat. Mach. Intell. 4(4): 414 (2022) - [c5]Zhiqiang Que, Marcus Loo, Hongxiang Fan, Maurizio Pierini, Alexander D. Tapper
Optimizing Graph Neural Networks for Jet Tagging in Particle Physics on FPGAs. FPL 2022: 327-333 - [d1]Mary Touranakou
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders: generator-level and reconstruction-level jets dataset. Zenodo, 2022 - [i38]Adrian Alan Pol, Thea Aarrestad
Lightweight Jet Reconstruction and Identification as an Object Detection Task. CoRR abs/2202.04499 (2022) - [i37]Joosep Pata, Javier M. Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone:
Machine Learning for Particle Flow Reconstruction at CMS. CoRR abs/2203.00330 (2022) - [i36]Mary Touranakou, Nadezda Chernyavskaya, Javier M. Duarte, Dimitrios Gunopoulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant:
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders. CoRR abs/2203.00520 (2022) - [i35]Shah Rukh Qasim, Nadezda Chernyavskaya, Jan Kieseler, Kenneth Long, Oleksandr Viazlo, Maurizio Pierini, Raheel Nawaz
End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks. CoRR abs/2204.01681 (2022) - [i34]Marco Letizia, Gianvito Losapio, Marco Rando
Learning new physics efficiently with nonparametric methods. CoRR abs/2204.02317 (2022) - [i33]Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini, Marcel Roed, Sioni Summers, Thea Aarrestad, Christoffer Petersson, Hampus Linander
Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. CoRR abs/2205.07690 (2022) - [i32]Zhiqiang Que, Marcus Loo, Hongxiang Fan, Michaela Blott, Maurizio Pierini, Alexander D. Tapper, Wayne Luk:
LL-GNN: Low Latency Graph Neural Networks on FPGAs for Particle Detectors. CoRR abs/2209.14065 (2022) - [i31]Ben Zandonati, Adrian Alan Pol, Maurizio Pierini, Olya Sirkin, Tal Kopetz:
FIT: A Metric for Model Sensitivity. CoRR abs/2210.08502 (2022) - [i30]Raghav Kansal, Anni Li, Javier M. Duarte, Nadezda Chernyavskaya, Maurizio Pierini, Breno Orzari, Thiago Tomei:
On the Evaluation of Generative Models in High Energy Physics. CoRR abs/2211.10295 (2022) - 2021
- [j8]Cheng Chen, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Analysis-Specific Fast Simulation at the LHC with Deep Learning. Comput. Softw. Big Sci. 5(1) (2021) - [j7]Jennifer Ngadiuba
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. Mach. Learn. Sci. Technol. 2(1): 15001 (2021) - [j6]Thea Aarrestad
Fast convolutional neural networks on FPGAs with hls4ml. Mach. Learn. Sci. Technol. 2(4): 45015 (2021) - [j5]Claudionor José Nunes Coelho Jr., Aki Kuusela, Shan Li, Hao Zhuang, Jennifer Ngadiuba
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors. Nat. Mach. Intell. 3(8): 675-686 (2021) - [c4]Zhiqiang Que, Erwei Wang, Umar Marikar, Eric A. Moreno
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. ASAP 2021: 117-124 - [c3]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. NeurIPS 2021: 23858-23871 - [i29]Thea Aarrestad
Fast convolutional neural networks on FPGAs with hls4ml. CoRR abs/2101.05108 (2021) - [i28]Joosep Pata, Javier M. Duarte
MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks. CoRR abs/2101.08578 (2021) - [i27]Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P. Carloni, Giuseppe Di Guglielmo, Philip C. Harris, Jeffrey D. Krupa, Dylan S. Rankin, Manuel Blanco Valentin, Josiah D. Hester, Yingyi Luo, John Mamish, Seda Ogrenci Memik, Thea Aarrestad
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. CoRR abs/2103.05579 (2021) - [i26]Giuseppe Di Guglielmo, Farah Fahim, Christian Herwig, Manuel Blanco Valentin, Javier M. Duarte
A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. CoRR abs/2105.01683 (2021) - [i25]Raghav Kansal, Javier M. Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopoulos:
Particle Cloud Generation with Message Passing Generative Adversarial Networks. CoRR abs/2106.11535 (2021) - [i24]Zhiqiang Que, Erwei Wang, Umar Marikar, Eric A. Moreno, Jennifer Ngadiuba, Hamza Javed, Bartlomiej Borzyszkowski, Thea Aarrestad, Vladimir Loncar, Sioni Summers, Maurizio Pierini, Peter Y. K. Cheung, Wayne Luk:
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. CoRR abs/2106.14089 (2021) - [i23]Eric A. Moreno, Jean-Roch Vlimant, Maria Spiropulu, Bartlomiej Borzyszkowski, Maurizio Pierini:
Source-Agnostic Gravitational-Wave Detection with Recurrent Autoencoders. CoRR abs/2107.12698 (2021) - [i22]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i21]Farouk Mokhtar, Raghav Kansal, Daniel Diaz
Explaining machine-learned particle-flow reconstruction. CoRR abs/2111.12840 (2021) - [i20]Steven Tsan, Raghav Kansal, Anthony Aportela, Daniel Diaz
Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance. CoRR abs/2111.12849 (2021) - [i19]Florencia Canelli, Annapaola de Cosa, Luc Le Pottier, Jeremi Niedziela
Autoencoders for Semivisible Jet Detection. CoRR abs/2112.02864 (2021) - 2020
- [j4]Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. Frontiers Big Data 3: 598927 (2020) - [i18]Sioni Summers, Giuseppe Di Guglielmo, Javier M. Duarte
Fast inference of Boosted Decision Trees in FPGAs for particle physics. CoRR abs/2002.02534 (2020) - [i17]Giuseppe Di Guglielmo, Javier M. Duarte
Compressing deep neural networks on FPGAs to binary and ternary precision with HLS4ML. CoRR abs/2003.06308 (2020) - [i16]Oliver Knapp, Günther Dissertori, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark. CoRR abs/2005.01598 (2020) - [i15]Claudionor José Nunes Coelho Jr., Aki Kuusela, Hao Zhuang, Thea Aarrestad
Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml. CoRR abs/2006.10159 (2020) - [i14]Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta, Jan Kieseler
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. CoRR abs/2008.03601 (2020) - [i13]Cheng Chen, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini:
Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning. CoRR abs/2010.01835 (2020) - [i12]Adrian Alan Pol, Victor Berger, Gianluca Cerminara, Cécile Germain, Maurizio Pierini:
Anomaly Detection With Conditional Variational Autoencoders. CoRR abs/2010.05531 (2020) - [i11]Raghav Kansal, Javier M. Duarte
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics. CoRR abs/2012.00173 (2020) - [i10]Aneesh Heintz, Vesal Razavimaleki, Javier M. Duarte
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. CoRR abs/2012.01563 (2020)
2010 – 2019
- 2019
- [j3]Javier M. Duarte
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. Comput. Softw. Big Sci. 3(1) (2019) - [j2]Thong Q. Nguyen
Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC. Comput. Softw. Big Sci. 3(1) (2019) - [j1]Adrian Alan Pol
Detector Monitoring with Artificial Neural Networks at the CMS Experiment at the CERN Large Hadron Collider. Comput. Softw. Big Sci. 3(1) (2019) - [c2]Javier M. Duarte, Song Han, Philip C. Harris, Sergo Jindariani, Edward Kreinar, Benjamin Kreis, Vladimir Loncar, Jennifer Ngadiuba, Maurizio Pierini, Dylan S. Rankin, Ryan A. Rivera, Sioni Summers, Nhan Tran, Zhenbin Wu:
Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. FPGA 2019: 305 - [c1]Adrian Alan Pol
Anomaly Detection with Conditional Variational Autoencoders. ICMLA 2019: 1651-1657 - [i9]Bobak Hashemi, Nick Amin, Kaustuv Datta
LHC analysis-specific datasets with Generative Adversarial Networks. CoRR abs/1901.05282 (2019) - [i8]Shah Rukh Qasim, Jan Kieseler
Learning representations of irregular particle-detector geometry with distance-weighted graph networks. CoRR abs/1902.07987 (2019) - [i7]Dawit Belayneh, Federico Carminati, Amir Farbin, Benjamin Hooberman, Gulrukh Khattak, Miaoyuan Liu, Junze Liu, Dominick Olivito, Vitória Barin Pacela, Maurizio Pierini, Alexander G. Schwing, Maria Spiropulu, Sofia Vallecorsa, Jean-Roch Vlimant, Wei Wei, Matt Zhang:
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics. CoRR abs/1912.06794 (2019) - 2018
- [i6]Javier M. Duarte
Fast inference of deep neural networks in FPGAs for particle physics. CoRR abs/1804.06913 (2018) - [i5]Thong Q. Nguyen
Topology classification with deep learning to improve real-time event selection at the LHC. CoRR abs/1807.00083 (2018) - [i4]Adrian Alan Pol, Gianluca Cerminara, Cécile Germain, Maurizio Pierini, Agrima Seth:
Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron Collider. CoRR abs/1808.00911 (2018) - [i3]Jesus Arjona Martinez, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant:
Pileup mitigation at the Large Hadron Collider with Graph Neural Networks. CoRR abs/1810.07988 (2018) - [i2]Olmo Cerri, Thong Q. Nguyen
Variational Autoencoders for New Physics Mining at the Large Hadron Collider. CoRR abs/1811.10276 (2018) - 2017
- [i1]V. Azzolini, Maxim Borisyak, Gianluca Cerminara, Denis Derkach, Giovanni Franzoni, F. De Guio, O. Koval, Maurizio Pierini, Adrian Alan Pol
Deep learning for inferring cause of data anomalies. CoRR abs/1711.07051 (2017)
Coauthor Index
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last updated on 2024-12-02 21:32 CET by the dblp team
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