Publikationsdatenbank

Letzte Einträge:
2021-01-25
10:08
OpenAccess [FZJ-2021-00716] Journal Article
; ;
Elastic form factors of nucleon excitations in lattice QCD
First principles calculations of the form factors of baryon excitations are now becoming accessible through advances in lattice-QCD techniques. In this paper, we explore the utility of the parity-expanded variational analysis (PEVA) technique in calculating the Sachs electromagnetic form factors for excitations of the proton and neutron. [...]
OpenAccess: Download fulltextPDF;
ddc:530

Details des Eintrags - Ähnliche Datensätze
2021-01-25
09:58
[FZJ-2021-00715] Conference Presentation (Other)
; ; ; et al
Role Of The Cost Function For Material Parameter Determination
Fire and Evacuation Modelling Technical Conference 2020, FEMTC 2020, virtualvirtual, virtual, 9 Sep 2020 - 11 Sep 20202020-09-092020-09-11
Inverse modelling of bench-scale experiments is a common method to determine material parameters for pyrolysis simulation, e.g. to compute flame spread. [...]
External link: Download fulltextFulltext

Details des Eintrags - Ähnliche Datensätze
2021-01-25
09:20
OpenAccess [FZJ-2021-00705] Journal Article
; ; ; et al
Bias evaluation and reduction in 3D OP-OSEM reconstruction in dynamic equilibrium PET studies with 11C-labeled for binding potential analysis
PLOS ONE 16(1), e0245580 - () [10.1371/journal.pone.0245580]
Iterative image reconstruction is widely used in positron emission tomography. However, it is known to contribute to quantitation bias and is particularly pronounced during dynamic studies with 11C-labeled radiotracers where count rates become low towards the end of the acquisition. [...]
OpenAccess: Download fulltextPDF;
ddc:610

Details des Eintrags - Ähnliche Datensätze
2021-01-25
09:11
[FZJ-2021-00704] Talk (non-conference) (Invited)

Structure, magnetism, and superconductivity in Fe-based superconductors
Seminar RWTH Aachen "Umhabilitation", ZOOM online meetingZOOM online meeting, ZOOM online meeting, 27 Jan 2021 - 27 Jan 20212021-01-272021-01-27
In iron-based high-temperature superconductors, magnetic fluctuations and magneto-elastic effects are believed to be important for the superconducting electron pairing mechanism. To gain insight into the interplay between the different ordering phenomena and the underlying couplings we studied the magnetic order and lattice distortion on AFe2As2 (A = Ca, Sr, Ba, Eu) single crystals by neutron and x-ray diffraction. [...]

Details des Eintrags - Ähnliche Datensätze
2021-01-24
17:13
[FZJ-2021-00684] Lecture (Other)

Introduction to Machine Learning and Deep Learning
Lecture at Course Scientific Image Processing of IHRS BioSoft (Jülich, Germany), 12 Feb 2020 - 12 Feb 20202020-02-122020-02-12
External link: Download fulltextFulltext

Details des Eintrags - Ähnliche Datensätze
2021-01-24
17:06
[FZJ-2021-00683] Conference Presentation (After Call)
; ; ; et al
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning
2020 IEEE Conference on Games (CoG), OsakaOsaka, Japan, 24 Aug 2020 - 27 Aug 20202020-08-242020-08-27
The Obstacle Tower Challenge is the task to master a procedurally generated chain of levels that subsequently get harder to complete. Whereas the most top performing entries of last year's competition used human demonstrations or reward shaping to learn how to cope with the challenge, we present an approach that performed competitively (placed 7th) but starts completely from scratch by means of Deep Reinforcement Learning with a relatively simple feed-forward deep network structure. [...]
External link: Download fulltextFulltext

Details des Eintrags - Ähnliche Datensätze
2021-01-24
16:59
[FZJ-2021-00682] Talk (non-conference) (Other)

Supercomputer Networking - Site-Update and Next Steps
CEA-JSC Annual Workshop, JülichJülich, Germany, 27 Feb 2020 - 28 Feb 20202020-02-272020-02-28

Details des Eintrags - Ähnliche Datensätze
2021-01-24
16:57
OpenAccess [FZJ-2021-00681] Contribution to a conference proceedings/Contribution to a book
; ; ; et al
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning
2020 IEEE Conference on Games (CoG) : [Proceedings] - IEEE, 2020
2020 IEEE Conference on Games (CoG), OsakaOsaka, Japan, 24 Aug 2020 - 27 Aug 20202020-08-242020-08-27
IEEE 447 - 454 () [10.1109/CoG47356.2020.9231802]
The Obstacle Tower Challenge is the task to master a procedurally generated chain of levels that subsequently get harder to complete. Whereas the most top performing entries of last year's competition used human demonstrations or reward shaping to learn how to cope with the challenge, we present an approach that performed competitively (placed 7th) but starts completely from scratch by means of Deep Reinforcement Learning with a relatively simple feed-forward deep network structure. [...]
OpenAccess: Download fulltextPDF;

Details des Eintrags - Ähnliche Datensätze
2021-01-24
16:54
[FZJ-2021-00680] Talk (non-conference) (Other)

Challenges in the Network-Design for Supercomputer-IO
HGF-Netzwerker-Treffen, JülichJülich, Germany, 20 Jan 2020 - 22 Jan 20202020-01-202020-01-22

Details des Eintrags - Ähnliche Datensätze
2021-01-23
13:15
[FZJ-2021-00676] Conference Presentation (Invited)

Materials, Interfaces and Processes – a Different Perspective on Neuromorphic Computing
Politecnico di Torino, Torino, onlineTorino, online, Italy, 7 Oct 2020 - 8 Oct 20202020-10-072020-10-08

Details des Eintrags - Ähnliche Datensätze