CUDA programs for solving the time-dependent dipolar Gross-Pitaevskii equation in an anisotropic trap. - Vladimir Loncar; Antun Balaz; Aleksandar Bogojevic; Srdjan Skrbic; Paulsamy Muruganandam; Sadhan K. Adhikari (Comput. Phys. Commun., 2016)

OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross-Pitaevskii equation. - Vladimir Loncar; Luis E. Young-S.; Srdjan Skrbic; Paulsamy Muruganandam; Sadhan K. Adhikari; Antun Balaz (Comput. Phys. Commun., 2016)

OpenMP GNU and Intel Fortran programs for solving the time-dependent Gross-Pitaevskii equation. - Luis E. Young-S.; Paulsamy Muruganandam; Sadhan K. Adhikari; Vladimir Loncar; Dusan Vudragovic; Antun Balaz (Comput. Phys. Commun., 2017)

Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. - Javier M. Duarte; Song Han 003; Philip C. Harris; Sergo Jindariani; Edward Kreinar; Benjamin Kreis; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Dylan S. Rankin; Ryan A. Rivera; Sioni Summers; et al. (FPGA, 2019)

C and Fortran OpenMP programs for rotating Bose-Einstein condensates. - Kishor Kumar Ramavarmaraja; Vladimir Loncar; Paulsamy Muruganandam; Sadhan K. Adhikari; Antun Balaz (Comput. Phys. Commun., 2019)

FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. - Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Sergo Jindariani; Suffian Khan; Benjamin Kreis; Brian Lee; Mia Liu; Vladimir Loncar; Jennifer Ngadiuba; et al. (Comput. Softw. Big Sci., 2019)

AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters. - Naif Tarafdar; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Vladimir Loncar; Dylan S. Rankin; Nhan Tran; Zhenbin Wu; Qianfeng Shen; Paul Chow (FCCM, 2020)

Fast inference of Boosted Decision Trees in FPGAs for particle physics. - Sioni Summers; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Duc Hoang; Sergo Jindariani; Edward Kreinar; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Dylan S. Rankin; Nhan Tran; et al. (CoRR, 2020)

Ultra Low-latency, Low-area Inference Accelerators using Heterogeneous Deep Quantization with QKeras and hls4ml. - Claudionor José Nunes Coelho Jr.; Aki Kuusela; Hao Zhuang 003; Thea Aarrestad; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Sioni Summers (CoRR, 2020)

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. - Aneesh Heintz; Vesal Razavimaleki; Javier M. Duarte; Gage DeZoort; Isobel Ojalvo; Savannah Thais; Markus Atkinson; Mark S. Neubauer; Lindsey Gray; Sergo Jindariani; Nhan Tran; Philip C. Harris; et al. (CoRR, 2020)

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. - Yutaro Iiyama; Gianluca Cerminara; Abhijay Gupta; Jan Kieseler; Vladimir Loncar; Maurizio Pierini; Shah Rukh Qasim; Marcel Rieger; Sioni Summers; Gerrit Van Onsem; Kinga Anna Wozniak; Jennifer Ngadiuba; et al. (Frontiers Big Data, 2020)

Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. - 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; et al. (ASAP, 2021)

Fast convolutional neural networks on FPGAs with hls4ml. - Thea Aarrestad; Vladimir Loncar; Maurizio Pierini; Sioni Summers; Jennifer Ngadiuba; Christoffer Petersson; Hampus Linander; Yutaro Iiyama; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Dylan S. Rankin; et al. (CoRR, 2021)

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. - 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; et al. (CoRR, 2021)

A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. - Giuseppe Di Guglielmo; Farah Fahim; Christian Herwig; Manuel Blanco Valentin; Javier M. Duarte; Cristian Gingu; Philip C. Harris; James Hirschauer; Martin Kwok; Vladimir Loncar; Yingyi Luo; Llovizna Miranda; et al. (CoRR, 2021)

Fast convolutional neural networks on FPGAs with hls4ml. - Thea Aarrestad; Vladimir Loncar; Nicolò Ghielmetti; Maurizio Pierini; Sioni Summers; Jennifer Ngadiuba; Christoffer Petersson; Hampus Linander; Yutaro Iiyama; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; et al. (Mach. Learn. Sci. Technol., 2021)

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. - Jennifer Ngadiuba; Vladimir Loncar; Maurizio Pierini; Sioni Summers; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Dylan S. Rankin; Sergo Jindariani; Mia Liu; Kevin Pedro; Nhan Tran; et al. (Mach. Learn. Sci. Technol., 2021)

Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors. - Claudionor José Nunes Coelho Jr.; Aki Kuusela; Shan Li; Hao Zhuang 003; Jennifer Ngadiuba; Thea Klaeboe Aarrestad; Vladimir Loncar; Maurizio Pierini; Adrian Alan Pol; Sioni Summers (Nat. Mach. Intell., 2021)

QONNX: Representing Arbitrary-Precision Quantized Neural Networks. - Alessandro Pappalardo; Yaman Umuroglu; Michaela Blott; Jovan Mitrevski; Benjamin Hawks; Nhan Tran; Vladimir Loncar; Sioni Summers; Hendrik Borras; Jules Muhizi; Matthew Trahms; Shih-Chieh Hsu; et al. (CoRR, 2022)

Lightweight jet reconstruction and identification as an object detection task. - Adrian Alan Pol; Thea Aarrestad; Ekaterina Govorkova; Roi Halily; Anat Klempner; Tal Kopetz; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Olya Sirkin; Sioni Summers (Mach. Learn. Sci. Technol., 2022)

Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. - Ekaterina Govorkova; Ema Puljak; Thea Aarrestad; Thomas James; Vladimir Loncar; Maurizio Pierini; Adrian Alan Pol; Nicolò Ghielmetti; Maksymilian Graczyk; Sioni Summers; Jennifer Ngadiuba; Thong Q. Nguyen; et al. (Nat. Mach. Intell., 2022)

Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. - Ekaterina Govorkova; Ema Puljak; Thea Aarrestad; Thomas James; Vladimir Loncar; Maurizio Pierini; Adrian Alan Pol; Nicolò Ghielmetti; Maksymilian Graczyk; Sioni Summers; Jennifer Ngadiuba; Thong Q. Nguyen; et al. (Nat. Mach. Intell., 2022)

AIgean: An Open Framework for Deploying Machine Learning on Heterogeneous Clusters. - Naif Tarafdar; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Vladimir Loncar; Dylan S. Rankin; Nhan Tran; Zhenbin Wu; Qianfeng Shen; Paul Chow (ACM Trans. Reconfigurable Technol. Syst., 2022)

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. - Nicolò Ghielmetti; Vladimir Loncar; Maurizio Pierini; Marcel Roed; Sioni Summers; Thea Aarrestad; Christoffer Petersson; Hampus Linander; Jennifer Ngadiuba; Kelvin Lin; Philip C. Harris (Mach. Learn. Sci. Technol., 2022)

Adapting Skip Connections for Resource-Efficient FPGA Inference. - Olivia Weng; Gabriel Marcano; Vladimir Loncar; Alireza Khodamoradi; Nojan Sheybani; Farinaz Koushanfar; Kristof Denolf; Javier Mauricio Duarte; Ryan Kastner (FPGA, 2023)

FPGA Resource-aware Structured Pruning for Real-Time Neural Networks. - Benjamin Ramhorst; Vladimir Loncar; George A. Constantinides (ICFPT, 2023)

Tailor: Altering Skip Connections for Resource-Efficient Inference. - Olivia Weng; Gabriel Marcano; Vladimir Loncar; Alireza Khodamoradi; Nojan Sheybani; Farinaz Koushanfar; Kristof Denolf; Javier Mauricio Duarte; Ryan Kastner (CoRR, 2023)

Symbolic Regression on FPGAs for Fast Machine Learning Inference. - Ho Fung Tsoi; Adrian Alan Pol; Vladimir Loncar; Ekaterina Govorkova; Miles D. Cranmer; Sridhara Dasu; Peter Elmer; Philip C. Harris; Isobel Ojalvo; Maurizio Pierini (CoRR, 2023)

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. - Elham E Khoda; Dylan S. Rankin; Rafael Teixeira de Lima; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu; Michael Kagan; Vladimir Loncar; Chaitanya Paikara; Richa Rao; Sioni Summers; Caterina Vernieri; et al. (Mach. Learn. Sci. Technol., 2023)

Reliable edge machine learning hardware for scientific applications. - Tommaso Baldi; Javier Campos; Benjamin Hawks; Jennifer Ngadiuba; Nhan Tran; Daniel Diaz 003; Javier M. Duarte; Ryan Kastner; Andres Meza 001; Melissa Quinnan; Olivia Weng; Caleb Geniesse; et al. (VTS, 2024)

SymbolNet: Neural Symbolic Regression with Adaptive Dynamic Pruning. - Ho Fung Tsoi; Vladimir Loncar; Sridhara Dasu; Philip C. Harris (CoRR, 2024)

Ultra Fast Transformers on FPGAs for Particle Physics Experiments. - Zhixing Jiang; Dennis Yin; Elham E Khoda; Vladimir Loncar; Ekaterina Govorkova; Eric A. Moreno; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu (CoRR, 2024)

Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. - 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; et al. (CoRR, 2024)

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip. - Chang Sun; Thea Klæboe Årrestad; Vladimir Loncar; Jennifer Ngadiuba; Maria Spiropulu (CoRR, 2024)

Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml. - Zhixing Jiang; Dennis Yin; Yihui Chen; Elham E Khoda; Scott Hauck; Shih-Chieh Hsu; Ekaterina Govorkova; Philip C. Harris; Vladimir Loncar; Eric A. Moreno (CoRR, 2024)

Ultrafast jet classification at the HL-LHC. - 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; et al. (Mach. Learn. Sci. Technol., 2024)

Tailor: Altering Skip Connections for Resource-Efficient Inference. - Olivia Weng; Gabriel Marcano; Vladimir Loncar; Alireza Khodamoradi; G. Abarajithan; Nojan Sheybani; Andres Meza 001; Farinaz Koushanfar; Kristof Denolf; Javier Mauricio Duarte; Ryan Kastner (ACM Trans. Reconfigurable Technol. Syst., 2024)

wa-hls4ml and lui-gnn: A Benchmark and GNN based Surrogate Model for hls4ml Resource and Latency Estimation. - Benjamin Hawks; Dennis Plotnikov; Nhan Tran; Karla Tame-Narvaez; Mohammad Mehdi Rahimifar; Hamza Ezzaoui Rahali; Audrey C. Therrien; Giuseppe Di Guglielmo; Javier Duarte; Vladimir Loncar (FPGA, 2025)

Comparative Analysis of FPGA and GPU Performance for Machine Learning-Based Track Reconstruction at LHCb. - Fotis I. Giasemis; Vladimir Loncar; Bertrand Granado; Vladimir Vava Gligorov (NewCAS, 2025)

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression. - Ho Fung Tsoi; Vladimir Loncar; Sridhara Dasu; Philip C. Harris (Mach. Learn. Sci. Technol., 2025)

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors. - Jakub Kvapil; Giorgian Borca-Tasciuc; H. Bossi; K. Chen; Y. Chen; Yasser Corrales Morales; H. Da Costa; C. Da Silva; C. Dean; J. Durham; S. Fu; Cong Hao; et al. (CoRR, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs. - Chang Sun; Zhiqiang Que; Vladimir Loncar; Wayne Luk; Maria Spiropulu (CoRR, 2025)

SymbolFit: Automatic Parametric Modeling with Symbolic Regression. - Ho Fung Tsoi; Dylan S. Rankin; Cecile Caillol; Miles D. Cranmer; Sridhara Dasu; Javier M. Duarte; Philip C. Harris; Elliot Lipeles; Vladimir Loncar (Comput. Softw. Big Sci., 2025)