nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
Accelerating IceCube’s Photon Propagation Code with CUDA
|
Schwanekamp, Hendrik |
|
|
|
1 |
|
artikel |
2 |
Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing
|
Cai, Tejin |
|
|
|
1 |
|
artikel |
3 |
A Common Tracking Software Project
|
Ai, Xiaocong |
|
|
|
1 |
|
artikel |
4 |
A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger
|
Aaij, R. |
|
|
|
1 |
|
artikel |
5 |
A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution
|
Sirunyan, A. M. |
|
|
|
1 |
|
artikel |
6 |
Advances in Computing in High Energy and Nuclear Physics—Invited Papers from vCHEP 2021
|
Bird, Ian |
|
|
|
1 |
|
artikel |
7 |
A Flexible and Efficient Approach to Missing Transverse Momentum Reconstruction
|
Balunas, William |
|
|
|
1 |
|
artikel |
8 |
A Generalized Approach to Longitudinal Momentum Determination in Cylindrical Straw Tube Detectors
|
Ikegami Andersson, Walter |
|
|
|
1 |
|
artikel |
9 |
A GPU-Based Kalman Filter for Track Fitting
|
Ai, Xiaocong |
|
|
|
1 |
|
artikel |
10 |
Allen: A High-Level Trigger on GPUs for LHCb
|
Aaij, R. |
|
|
|
1 |
|
artikel |
11 |
Analysis-Specific Fast Simulation at the LHC with Deep Learning
|
Chen, C. |
|
|
|
1 |
|
artikel |
12 |
Analyzing WLCG File Transfer Errors Through Machine Learning
|
Clissa, Luca |
|
|
|
1 |
|
artikel |
13 |
A Pattern Recognition Algorithm for Quantum Annealers
|
Bapst, Frédéric |
|
|
|
1 |
p. 1-7 |
artikel |
14 |
A Pattern Recognition Algorithm for Quantum Annealers
|
Bapst, Frédéric |
|
|
|
1 |
|
artikel |
15 |
A Roadmap for HEP Software and Computing R&D for the 2020s
|
Albrecht, Johannes |
|
|
|
1 |
p. 1-49 |
artikel |
16 |
A Roadmap for HEP Software and Computing R&D for the 2020s
|
Elsen, Eckhard |
|
|
|
1 |
p. 1-2 |
artikel |
17 |
Artificial Intelligence for the Electron Ion Collider (AI4EIC)
|
Allaire, C. |
|
|
|
1 |
|
artikel |
18 |
Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters
|
Aad, Georges |
|
|
|
1 |
|
artikel |
19 |
AtlFast3: The Next Generation of Fast Simulation in ATLAS
|
Aad, G. |
|
|
|
1 |
|
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 |
|
|
|
1 |
p. 1-2 |
artikel |
22 |
Cait: Analysis Toolkit for Cryogenic Particle Detectors in Python
|
Wagner, Felix |
|
|
|
1 |
|
artikel |
23 |
Challenges in Monte Carlo Event Generator Software for High-Luminosity LHC
|
, |
|
|
|
1 |
|
artikel |
24 |
Charged Particle Tracking via Edge-Classifying Interaction Networks
|
DeZoort, Gage |
|
|
|
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 |
|
|
|
1 |
|
artikel |
27 |
Constraints on Future Analysis Metadata Systems in High Energy Physics
|
Khoo, T. J. |
|
|
|
1 |
|
artikel |
28 |
Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition
|
Maglianella, Leandro |
|
|
|
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 |
|
|
|
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 |