| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Accelerating IceCube’s Photon Propagation Code with CUDA
|
Schwanekamp, Hendrik
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1 |
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artikel
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| 2 |
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing
|
Cai, Tejin
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1 |
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artikel
|
| 3 |
A Common Tracking Software Project
|
Ai, Xiaocong
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1 |
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artikel
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| 4 |
A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger
|
Aaij, R.
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1 |
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artikel
|
| 5 |
A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution
|
Sirunyan, A. M.
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1 |
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artikel
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| 6 |
Advances in Computing in High Energy and Nuclear Physics—Invited Papers from vCHEP 2021
|
Bird, Ian
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1 |
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artikel
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| 7 |
A Flexible and Efficient Approach to Missing Transverse Momentum Reconstruction
|
Balunas, William
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1 |
|
artikel
|
| 8 |
A Generalized Approach to Longitudinal Momentum Determination in Cylindrical Straw Tube Detectors
|
Ikegami Andersson, Walter
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1 |
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artikel
|
| 9 |
A GPU-Based Kalman Filter for Track Fitting
|
Ai, Xiaocong
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1 |
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artikel
|
| 10 |
Allen: A High-Level Trigger on GPUs for LHCb
|
Aaij, R.
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1 |
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artikel
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| 11 |
Analysis-Specific Fast Simulation at the LHC with Deep Learning
|
Chen, C.
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1 |
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artikel
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| 12 |
Analyzing WLCG File Transfer Errors Through Machine Learning
|
Clissa, Luca
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1 |
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artikel
|
| 13 |
A Pattern Recognition Algorithm for Quantum Annealers
|
Bapst, Frédéric
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1 |
p. 1-7
|
artikel
|
| 14 |
A Pattern Recognition Algorithm for Quantum Annealers
|
Bapst, Frédéric
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1 |
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artikel
|
| 15 |
A Roadmap for HEP Software and Computing R&D for the 2020s
|
Albrecht, Johannes
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1 |
p. 1-49
|
artikel
|
| 16 |
A Roadmap for HEP Software and Computing R&D for the 2020s
|
Elsen, Eckhard
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1 |
p. 1-2
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artikel
|
| 17 |
Artificial Intelligence for the Electron Ion Collider (AI4EIC)
|
Allaire, C.
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1 |
|
artikel
|
| 18 |
Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters
|
Aad, Georges
|
|
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1 |
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artikel
|
| 19 |
AtlFast3: The Next Generation of Fast Simulation in ATLAS
|
Aad, G.
|
|
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|
1 |
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artikel
|
| 20 |
B2BII: Data Conversion from Belle to Belle II
|
Gelb, Moritz
|
|
2018
|
|
1 |
p. 1-7
|
artikel
|
| 21 |
Big Data Challenges in Big Science
|
Heiss, Andreas
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|
1 |
p. 1-2
|
artikel
|
| 22 |
Cait: Analysis Toolkit for Cryogenic Particle Detectors in Python
|
Wagner, Felix
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1 |
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artikel
|
| 23 |
Challenges in Monte Carlo Event Generator Software for High-Luminosity LHC
|
,
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1 |
|
artikel
|
| 24 |
Charged Particle Tracking via Edge-Classifying Interaction Networks
|
DeZoort, Gage
|
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|
1 |
|
artikel
|
| 25 |
CMS@home: Integrating the Volunteer Cloud and High-Throughput Computing
|
Field, L.
|
|
2018
|
|
1 |
p. 1-8
|
artikel
|
| 26 |
Computational Challenges for Multi-loop Collider Phenomenology
|
Cordero, Fernando Febres
|
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1 |
|
artikel
|
| 27 |
Constraints on Future Analysis Metadata Systems in High Energy Physics
|
Khoo, T. J.
|
|
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1 |
|
artikel
|
| 28 |
Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition
|
Maglianella, Leandro
|
|
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|
1 |
|
artikel
|
| 29 |
Correction to: The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC
|
Kuznetsov, Valentin
|
|
|
|
1 |
p. 1-9
|
artikel
|
| 30 |
Correction to: Using ATLAS@Home to Exploit Extra CPU from Busy Grid Sites
|
Wu, Wenjing
|
|
|
|
1 |
p. 1
|
artikel
|
| 31 |
CSBS Editorial
|
Beckmann, Volker
|
|
2017
|
|
1 |
p. 1-3
|
artikel
|
| 32 |
Deep Generative Models for Fast Photon Shower Simulation in ATLAS
|
,
|
|
|
|
1 |
|
artikel
|
| 33 |
Deep Learning Strategies for ProtoDUNE Raw Data Denoising
|
Rossi, Marco
|
|
|
|
1 |
|
artikel
|
| 34 |
Detector Monitoring with Artificial Neural Networks at the CMS Experiment at the CERN Large Hadron Collider
|
Pol, Adrian Alan
|
|
|
|
1 |
p. 1-13
|
artikel
|
| 35 |
Dynamic Distribution of High-Rate Data Processing from CERN to Remote HPC Data Centers
|
Boccali, T.
|
|
|
|
1 |
|
artikel
|
| 36 |
Dynamic Virtualized Deployment of Particle Physics Environments on a High Performance Computing Cluster
|
Bührer, Felix
|
|
|
|
1 |
p. 1-7
|
artikel
|
| 37 |
Dynamo: Handling Scientific Data Across Sites and Storage Media
|
Iiyama, Yutaro
|
|
|
|
1 |
|
artikel
|
| 38 |
Education and Training for Software Developers in Particle Physics
|
Kluth, Stefan
|
|
|
|
1 |
|
artikel
|
| 39 |
Efficiency Parameterization with Neural Networks
|
Di Bello, Francesco Armando
|
|
|
|
1 |
|
artikel
|
| 40 |
Emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events
|
Aad, G.
|
|
|
|
1 |
|
artikel
|
| 41 |
End-to-End Physics Event Classification with CMS Open Data: Applying Image-Based Deep Learning to Detector Data for the Direct Classification of Collision Events at the LHC
|
Andrews, M.
|
|
|
|
1 |
|
artikel
|
| 42 |
Evaluating CephFS Performance vs. Cost on High-Density Commodity Disk Servers
|
Peters, Andreas J.
|
|
|
|
1 |
|
artikel
|
| 43 |
Event Classification with Quantum Machine Learning in High-Energy Physics
|
Terashi, Koji
|
|
|
|
1 |
|
artikel
|
| 44 |
Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks
|
Musella, Pasquale
|
|
2018
|
|
1 |
p. 1-11
|
artikel
|
| 45 |
FastBDT: A Speed-Optimized Multivariate Classification Algorithm for the Belle II Experiment
|
Keck, Thomas
|
|
2017
|
|
1 |
p. 1-11
|
artikel
|
| 46 |
Fast Columnar Physics Analyses of Terabyte-Scale LHC Data on a Cache-Aware Dask Cluster
|
Eich, Niclas
|
|
|
|
1 |
|
artikel
|
| 47 |
Fast Simulation for the Super Charm-Tau Factory Detector
|
Barnyakov, Alexander
|
|
|
|
1 |
|
artikel
|
| 48 |
FITS Data Source for Apache Spark
|
Peloton, Julien
|
|
2018
|
|
1 |
p. 1-9
|
artikel
|
| 49 |
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing
|
Duarte, Javier
|
|
|
|
1 |
p. 1-15
|
artikel
|
| 50 |
Full Detector Simulation with Unprecedented Background Occupancy at a Muon Collider
|
Bartosik, Nazar
|
|
|
|
1 |
|
artikel
|
| 51 |
FunTuple: A New N-tuple Component for Offline Data Processing at the LHCb Experiment
|
Mathad, Abhijit
|
|
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|
1 |
|
artikel
|
| 52 |
Future Trends in Nuclear Physics Computing
|
Diefenthaler, Markus
|
|
|
|
1 |
|
artikel
|
| 53 |
GeantV
|
Amadio, G.
|
|
|
|
1 |
|
artikel
|
| 54 |
Generating and Refining Particle Detector Simulations Using the Wasserstein Distance in Adversarial Networks
|
Erdmann, Martin
|
|
2018
|
|
1 |
p. 1-9
|
artikel
|
| 55 |
Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed
|
Buhmann, Erik
|
|
|
|
1 |
|
artikel
|
| 56 |
GNN for Deep Full Event Interpretation and Hierarchical Reconstruction of Heavy-Hadron Decays in Proton–Proton Collisions
|
García Pardiñas, Julián
|
|
|
|
1 |
|
artikel
|
| 57 |
HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation
|
Holzman, Burt
|
|
2017
|
|
1 |
p. 1-15
|
artikel
|
| 58 |
HEPiX Benchmarking Solution for WLCG Computing Resources
|
Giordano, Domenico
|
|
|
|
1 |
|
artikel
|
| 59 |
High-Throughput Cloud Computing with the Cloudscheduler VM Provisioning Service
|
Berghaus, F.
|
|
|
|
1 |
|
artikel
|
| 60 |
High-Throughput Cloud Computing with the Cloudscheduler VM Provisioning Service
|
Berghaus, F.
|
|
|
|
1 |
|
artikel
|
| 61 |
Identifying the Relevant Dependencies of the Neural Network Response on Characteristics of the Input Space
|
Wunsch, Stefan
|
|
2018
|
|
1 |
p. 1-7
|
artikel
|
| 62 |
Implementation of ACTS into sPHENIX Track Reconstruction
|
Osborn, Joseph D.
|
|
|
|
1 |
|
artikel
|
| 63 |
Improving Robustness of Jet Tagging Algorithms with Adversarial Training
|
Stein, Annika
|
|
|
|
1 |
|
artikel
|
| 64 |
Interactive analysis notebooks on DESY batch resources
|
Reppin, J.
|
|
|
|
1 |
|
artikel
|
| 65 |
Jet Energy Calibration with Deep Learning as a Kubeflow Pipeline
|
Holmberg, Daniel
|
|
|
|
1 |
|
artikel
|
| 66 |
KinFit: A Kinematic Fitting Package for Hadron Physics Experiments
|
Esmail, Waleed
|
|
|
|
1 |
|
artikel
|
| 67 |
Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis
|
de Oliveira, Luke
|
|
2017
|
|
1 |
p. 1-24
|
artikel
|
| 68 |
Lightweight Integration of a Data Cache for Opportunistic Usage of HPC Resources in HEP Workflows
|
Sammel, Dirk
|
|
|
|
1 |
|
artikel
|
| 69 |
Machine Learning Pipelines with Modern Big Data Tools for High Energy Physics
|
Migliorini, M.
|
|
|
|
1 |
|
artikel
|
| 70 |
MadMiner: Machine Learning-Based Inference for Particle Physics
|
Brehmer, Johann
|
|
|
|
1 |
|
artikel
|
| 71 |
MLaaS4HEP: Machine Learning as a Service for HEP
|
Kuznetsov, Valentin
|
|
|
|
1 |
|
artikel
|
| 72 |
Modelling Large-Scale Scientific Data Transfers
|
Bogado, Joaquin
|
|
|
|
1 |
|
artikel
|
| 73 |
Ntuple Wizard: An Application to Access Large-Scale Open Data from LHCb
|
Aidala, Christine A.
|
|
|
|
1 |
|
artikel
|
| 74 |
Operating an HPC/HTC Cluster with Fully Containerized Jobs Using HTCondor, Singularity, CephFS and CVMFS
|
Freyermuth, Oliver
|
|
|
|
1 |
|
artikel
|
| 75 |
Optimal Statistical Inference in the Presence of Systematic Uncertainties Using Neural Network Optimization Based on Binned Poisson Likelihoods with Nuisance Parameters
|
Wunsch, Stefan
|
|
|
|
1 |
|
artikel
|
| 76 |
Optimizing Cherenkov Photons Generation and Propagation in CORSIKA for CTA Monte–Carlo Simulations
|
Arrabito, Luisa
|
|
|
|
1 |
|
artikel
|
| 77 |
PanDA: Production and Distributed Analysis System
|
Maeno, Tadashi
|
|
|
|
1 |
|
artikel
|
| 78 |
Parametric Optimization on HPC Clusters with Geneva
|
Weßner, Jonas
|
|
|
|
1 |
|
artikel
|
| 79 |
Performance of Julia for High Energy Physics Analyses
|
Stanitzki, Marcel
|
|
|
|
1 |
|
artikel
|
| 80 |
Photon Reconstruction in the Belle II Calorimeter Using Graph Neural Networks
|
Wemmer, F.
|
|
|
|
1 |
|
artikel
|
| 81 |
Polynomial Data Compression for Large-Scale Physics Experiments
|
Aubert, Pierre
|
|
2018
|
|
1 |
p. 1-9
|
artikel
|
| 82 |
Potential of the Julia Programming Language for High Energy Physics Computing
|
Eschle, Jonas
|
|
|
|
1 |
|
artikel
|
| 83 |
Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network
|
Erdmann, Martin
|
|
|
|
1 |
p. 1-13
|
artikel
|
| 84 |
Quantum Algorithms for Charged Particle Track Reconstruction in the LUXE Experiment
|
Crippa, Arianna
|
|
|
|
1 |
|
artikel
|
| 85 |
Quantum Computing: Advancing Fundamental Physics
|
Spentzouris, Panagiotis
|
|
|
|
1 |
|
artikel
|
| 86 |
Quantum Support Vector Machines for Continuum Suppression in B Meson Decays
|
Heredge, Jamie
|
|
|
|
1 |
|
artikel
|
| 87 |
Real-Time Graph Building on FPGAs for Machine Learning Trigger Applications in Particle Physics
|
Neu, Marc
|
|
|
|
1 |
|
artikel
|
| 88 |
Recursive Neural Networks in Quark/Gluon Tagging
|
Cheng, Taoli
|
|
2018
|
|
1 |
p. 1-13
|
artikel
|
| 89 |
Reducing the Dependence of the Neural Network Function to Systematic Uncertainties in the Input Space
|
Wunsch, Stefan
|
|
|
|
1 |
|
artikel
|
| 90 |
Reducing the Dependence of the Neural Network Function to Systematic Uncertainties in the Input Space
|
Wunsch, Stefan
|
|
|
|
1 |
|
artikel
|
| 91 |
Review of High-Quality Random Number Generators
|
James, Frederick
|
|
|
|
1 |
|
artikel
|
| 92 |
Review of High-Quality Random Number Generators
|
James, Frederick
|
|
|
|
1 |
|
artikel
|
| 93 |
Rucio: Scientific Data Management
|
Barisits, Martin
|
|
|
|
1 |
p. 1-19
|
artikel
|
| 94 |
Shared Data and Algorithms for Deep Learning in Fundamental Physics
|
Benato, Lisa
|
|
|
|
1 |
|
artikel
|
| 95 |
Simulation and Evaluation of Cloud Storage Caching for Data Intensive Science
|
Wegner, Tobias
|
|
|
|
1 |
|
artikel
|
| 96 |
Simulation of Dielectric Axion Haloscopes with Deep Neural Networks: A Proof-of-Principle
|
Jung, Philipp Alexander
|
|
|
|
1 |
|
artikel
|
| 97 |
Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access
|
Bhimji, W.
|
|
|
|
1 |
|
artikel
|
| 98 |
Software Performance of the ATLAS Track Reconstruction for LHC Run 3
|
,
|
|
|
|
1 |
|
artikel
|
| 99 |
Software Training in HEP
|
Malik, Sudhir
|
|
|
|
1 |
|
artikel
|
| 100 |
Studying the Potential of Graphcore® IPUs for Applications in Particle Physics
|
Maddrell-Mander, Samuel
|
|
|
|
1 |
|
artikel
|
| 101 |
Supporting High-Performance and High-Throughput Computing for Experimental Science
|
Huerta, E. A.
|
|
|
|
1 |
p. 1-15
|
artikel
|
| 102 |
Survey of Open Data Concepts Within Fundamental Physics: An Initiative of the PUNCH4NFDI Consortium
|
Enke, Harry
|
|
|
|
1 |
|
artikel
|
| 103 |
The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC
|
Kuznetsov, Valentin
|
|
2018
|
|
1 |
p. 1-9
|
artikel
|
| 104 |
The ATLAS EventIndex
|
Barberis, Dario
|
|
|
|
1 |
|
artikel
|
| 105 |
The Belle II Core Software
|
Kuhr, T.
|
|
|
|
1 |
p. 1-12
|
artikel
|
| 106 |
The Belle II Online–Offline Data Operations System
|
Barrett, Matthew
|
|
|
|
1 |
|
artikel
|
| 107 |
The CMS monitoring infrastructure and applications
|
Ariza-Porras, Christian
|
|
|
|
1 |
|
artikel
|
| 108 |
The Full Event Interpretation
|
Keck, T.
|
|
|
|
1 |
p. 1-10
|
artikel
|
| 109 |
The Tracking Machine Learning Challenge: Throughput Phase
|
Amrouche, Sabrina
|
|
|
|
1 |
|
artikel
|
| 110 |
Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC
|
Nguyen, T. Q.
|
|
|
|
1 |
p. 1-14
|
artikel
|
| 111 |
Towards A Next Generation of CORSIKA: A Framework for the Simulation of Particle Cascades in Astroparticle Physics
|
Engel, Ralph
|
|
|
|
1 |
p. 1-12
|
artikel
|
| 112 |
Unleashing JupyterHub: Exploiting Resources Without Inbound Network Connectivity Using HTCondor
|
Freyermuth, Oliver
|
|
|
|
1 |
|
artikel
|
| 113 |
Using ATLAS@Home to Exploit Extra CPU from Busy Grid Sites
|
Wu, Wenjing
|
|
|
|
1 |
p. 1-7
|
artikel
|
| 114 |
When, Where, and How to Open Data: a Personal Perspective
|
Nachman, Benjamin
|
|
|
|
1 |
|
artikel
|
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