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Naslov Ultrafast jet classification at the HL-LHC (Article)
Autori Odagiu Patrick ... Loncar Vladimir ... (broj koautora 16) 
Info MACHINE LEARNING-SCIENCE AND TECHNOLOGY, (2024), vol. 5 br. 3, str. -
Projekat NSF; Swiss National Science Foundation [PZ00P2_201594]; European Research Council (ERC) under the European Union [966696]; U.S. Department of Energy (DOE), Office of Science, Office of High Energy Physics Early Career Research program [DE-SC0021187]; CAPES; CNPq; FAPERJ; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [EXC 2121, 390833306]; Fermi Research Alliance, LLC [DE-AC02-07CH11359]; Department of Energy (DOE), Office of Science, Office of High Energy Physics; U.S. Department of Energy (DOE), Office of Science, Office of High Energy Physics 'Designing efficient edge AI with physics phenomena' Project [DE-FOA-0002705]; United Kingdom EPSRC [EP/V028251/1, EP/L016796/1, EP/N031768/1, EP/P010040/1, EP/S030069/1]
Ispravka Web of Science   Članak   Elečas   Rang časopisa  
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Naslov Symbolic Regression on FPGAs for Fast Machine Learning Inference (Proceedings Paper)
Autori Tsoi Ho Fung Pol Adrian Alan Loncar Vladimir Govorkova Ekaterina Cranmer Miles Dasu Sridhara Elmer Peter Harris Philip Ojalvo Isobel Pierini Maurizio 
Info 26TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS, CHEP 2023, (2024), vol. 295 br. , str. -
Projekat U.S. Department of Energy [DE-SC0017647]; Eric and Wendy Schmidt Transformative Technology Fund [A3D3, NSF 2117997]; European Research Council (ERC) under the European Union [772369]
Ispravka Web of Science   Članak   Elečas  
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Naslov FPGA Resource-aware Structured Pruning for Real-Time Neural Networks (Proceedings Paper)
Autori Ramhorst Benjamin Loncar Vladimir Constantinides George A 
Info 2023 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE TECHNOLOGY, ICFPT, (2023), vol. br. , str. 282-283
Projekat Engineering and Physical Sciences Research Council (EPSRC) [EP/S030069/1]; NSF Institute [A3D3]; NSF [2117997]
Ispravka Web of Science   Članak  
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Naslov Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml (Article)
Autori Ghielmetti Nicolo Loncar Vladimir Pierini Maurizio Roed Marcel Summers Sioni Aarrestad Thea Petersson Christoffer Linander Hampus Ngadiuba Jennifer Lin Kelvin Harris Philip 
Info MACHINE LEARNING-SCIENCE AND TECHNOLOGY, (2022), vol. 3 br. 4, str. -
Projekat European Research Council (ERC) [772369, 966696]
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science   Scopus  
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Naslov Lightweight jet reconstruction and identification as an object detection task (Article)
Autori Pol Adrian Alan Aarrestad Thea Govorkova Ekaterina Halily Roi Klempner Anat Kopetz Tal Loncar Vladimir Ngadiuba Jennifer Pierini Maurizio Sirkin Olya Summers Sioni 
Info MACHINE LEARNING-SCIENCE AND TECHNOLOGY, (2022), vol. 3 br. 2, str. -
Projekat European Research Council (ERC) under the European Union [772369]; CEVA under the CERN Knowledge Transfer Group
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science   Scopus  
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Naslov Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider (Article)
Autori Govorkova Ekaterina Puljak Ema Aarrestad Thea James Thomas Loncar Vladimir Pierini Maurizio Pol Adrian Alan Ghielmetti Nicolo Graczyk Maksymilian Summers Sioni Ngadiuba Jennifer Nguyen Thong Q Duarte Javier Wu Zhenbin 
Info NATURE MACHINE INTELLIGENCE, (2022), vol. 4 br. 2, str. 154-+
Projekat European Research Council (ERC) under the European UnionEuropean Research Council (ERC) [772369]; ERC-POC programme [996696]
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science  
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Naslov A Reconfigurable Neural Network ASIC for Detector Front-End Data Compression at the HL-LHC (Article)
Autori Di Guglielmo Giuseppe ... Loncar Vladimir ... (broj koautora 18) 
Info IEEE TRANSACTIONS ON NUCLEAR SCIENCE, (2021), vol. 68 br. 8, str. 2179-2186
Projekat Fermi Research Alliance, LLC through the U.S. Department of Energy (DOE), Office of Science, Office of High Energy Physics [DE-AC02-07CH11359]; DOE, Office of Science, Office of High Energy Physics Early Career Research ProgramUnited States Department of
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science   Scopus  
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Naslov Fast convolutional neural networks on FPGAs with hls4ml (Article)
Autori Aarrestad Thea Loncar Vladimir ... (broj koautora 20) 
Info MACHINE LEARNING-SCIENCE AND TECHNOLOGY, (2021), vol. 2 br. 4, str. -
Projekat European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [772369]; Fermi Research Alliance, LLC [DE-AC02-07CH11359]; U.S. Department of Energy (DOE), Office of Science, Office of High Energy Physics; Massachusetts Institute of Technology University; National Science Foundation [1606321, 115164]; DOE, Office of Science, Office of High Energy Physics Early Career Research program [DE-SC0021187]
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science  
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Naslov Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors (Article)
Autori Coelho Claudionor N Jr Kuusela Aki Li Shan Zhuang Hao Ngadiuba Jennifer Aarrestad Thea Klaeboe Loncar Vladimir Pierini Maurizio Pol Adrian Alan Summers Sioni 
Info NATURE MACHINE INTELLIGENCE, (2021), vol. 3 br. 8, str. 675-+
Projekat European Research Council (ERC) [772369]; Zenseact under the CERN Knowledge Transfer Group; CEVA under the CERN Knowledge Transfer Group
Ispravka Web of Science   Članak   Elečas   Rang časopisa   Citati: Web of Science   Scopus  
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Naslov Generative Adversarial Networks for fast simulation (Proceedings Paper)
Autori Carminati Federico Khattak Gulrukh Loncar Vladimir Nguyen Thong Q Pierini Maurizio Da Rocha Ricardo Brito Samaras-Tsakiris Konstantinos Vallecorsa Sofia Vlimant Jean-Roch 
Info 19TH INTERNATIONAL WORKSHOP ON ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH, (2020), vol. 1525 br. , str. -
Ispravka Web of Science   Članak   Elečas   Citati: Web of Science   Scopus  
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