Publications | Frank-Peter Schilling

GoogleScholar ORCID Inspire arXiv

The following list contains only my most important publications. For a full list of my publications, see e.g. GoogleScholar. My h-index is approx. 165.

2026

AI for
Med. Imaging

MInDI-3D: Iterative Deep Learning in 3D for Sparse-View Cone Beam Computed Tomography

Daniel Barco, Marc Stadelmann, Martin Oswald, Ivo Herzig, and 6 more authors

IEEE Access, 2026

Bib DOI File arXiv

@article{mindi3d2025,
  author = {Barco, Daniel and Stadelmann, Marc and Oswald, Martin and Herzig, Ivo and Lichtensteiger, Lukas and Paysan, Pascal and Peterlik, Igor and Walczak, Michal and Menze, Bjoern and Schilling, Frank-Peter},
  journal = {IEEE Access},
  title = {MInDI-3D: Iterative Deep Learning in 3D for Sparse-View Cone Beam Computed Tomography},
  year = {2026},
  volume = {14},
  number = {},
  pages = {6438-6449},
  doi = {10.1109/ACCESS.2026.3652627},
  eprint = {2508.09616},
  archiveprefix = {arXiv},
}

Optimization of Deep Learning Models for Radio Galaxy Classification

Philipp Denzel, Manuel Weiss, Elena Gavagnin, and Frank-Peter Schilling

2026

DOI URL File arXiv
GenAI for
Astrophysics

Galactic Alchemy: Deep Learning Map-to-Map Translation in Hydrodynamical Simulations

Philipp Denzel, Yann Billeter, Frank-Peter Schilling, and Elena Gavagnin

Monthly Notices of the Royal Astronomical Society, Feb 2026

DOI URL File arXiv

2025

Assessment tool for trustworthy AI systems: operational workflows for compliance assessment with regulatory requirements

Carmen Frischknecht-Gruber, Philipp Denzel, Oliver Forster, Yann Billeter, and 6 more authors

In AI Days @ HES-SO, Geneva and Lausanne, Switzerland, Feb 2025

URL File
AI Assessment

AI Assessment in Practice: Implementing a Certification Scheme for AI Trustworthiness

Carmen Frischknecht-Gruber, Philipp Denzel, Monika Reif, Yann Billeter, and 5 more authors

In Symposium on Scaling AI Assessments (SAIA 2024), Feb 2025

DOI File

2024

SDS 2024

Towards the Certification of AI-based Systems

Philipp Denzel, Stefan Brunner, Yann Billeter, Oliver Forster, and 8 more authors

In SDS 2024: 11th IEEE Swiss Conference on Data Science, Feb 2024

DOI File
SDS 2024

MLOps as Enabler of Trustworthy AI

Yann Billeter, Philipp Denzel, Ricardo Chavarriaga, Oliver Forster, and 5 more authors

In SDS 2024: 11th IEEE Swiss Conference on Data Science, Feb 2024

DOI File
ESREL 2024

Certification Scheme For Artificial Intelligence Based Systems

Yann Billeter, Stefan Brunner, Ricardo Chavarriaga, Philipp Denzel, and 7 more authors

In ESREL 2024: Advances in Reliability, Safety and Security, Feb 2024

DOI File
IEEE Access
Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning - A Review

Mohammadreza Amirian, Daniel Barco, Ivo Herzig, and Frank-Peter Schilling

IEEE Access, Feb 2024

Abs Bib DOI File arXiv

Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image-guided radiation therapy, implant dentistry or orthopaedics. While deep learning methods have been applied to reduce various types of CBCT image artifacts arising from motion, metal objects, or low-dose acquisition, a comprehensive review summarizing the successes and shortcomings of these approaches, with a primary focus on the type of artifacts rather than the architecture of neural networks, is lacking in the literature. In this review, the data generation and simulation pipelines, as well as artifact reduction techniques are specifically investigated for each type of artifact. We provide an overview of deep learning techniques that have successfully been shown to reduce artifacts in 3D, as well as in time-resolved (4D) CBCT through the use of projection- and/or volume-domain optimizations, or by introducing neural networks directly within the CBCT reconstruction algorithms. Research gaps are identified to suggest avenues for future exploration. One of the key findings of this work is an observed trend towards the use of generative models including GANs and score-based or diffusion models, accompanied with the need for more diverse and open training datasets and simulations.
@article{amirian_2024, author = {Amirian, Mohammadreza and Barco, Daniel and Herzig, Ivo and Schilling, Frank-Peter}, journal = {IEEE Access}, title = {{Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning - A Review}}, year = {2024}, issn = {2169-3536}, pages = {10281-10295}, volume = {12}, doi = {10.1109/ACCESS.2024.3353195}, eprint = {2403.18565}, eprinttype = {arXiv}, modificationdate = {2024-01-21T18:04:49}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)} }

2023

A framework for assessing and certifying explainability of health-oriented AI systems

Philipp Denzel, Stefan Brunner, Paul-Philipp Luley, Carmen Frischknecht-Gruber, and 7 more authors

Feb 2023

URL File
Map-to-map translation for SKA mock observations and cosmological simulations

Philipp Denzel, Frank-Peter Schilling, and Elena Gavagnin

In Hammers and Nails 2023 - Swiss Edition, Ascona, Switzerland, October 2023, Feb 2023

DOI File
Med.Phys.
Mitigation of motion-induced artefacts in Cone Beam Computed Tomography using Deep Convolutional Neural Networks

Mohammadreza Amirian, Javier A. Montoya-Zegarra, Ivo Herzig, Peter Eggenberger Hotz, and 9 more authors

Med. Phys., Feb 2023

Abs Bib DOI File

Background: Cone beam computed tomography (CBCT) is often employed on radiation therapy treatment devices (linear accelerators) used in image-guided radiation therapy (IGRT). For each treatment session, it is necessary to obtain the image of the day in order to accurately position the patient and to enable adaptive treatment capabilities including auto-segmentation and dose calculation. Reconstructed CBCT images often suffer from artifacts, in particular those induced by patient motion. Deep-learning based approaches promise ways to mitigate such artifacts. Purpose: We propose a novel deep-learning based approach with the goal to reduce motion induced artifacts in CBCT images and improve image quality. It is based on supervised learning and includes neural network architectures employed as pre- and/or post-processing steps during CBCT reconstruction. Methods: Our approach is based on deep convolutional neural networks which complement the standard CBCT reconstruction, which is performed either with the analytical Feldkamp-Davis-Kress (FDK) method, or with an iterative algebraic reconstruction technique (SART-TV). The neural networks, which are based on refined U-net architectures, are trained end-to-end in a supervised learning setup. Labeled training data are obtained by means of a motion simulation, which uses the two extreme phases of 4D CT scans, their deformation vector fields, as well as time-dependent amplitude signals as input. The trained networks are validated against ground truth using quantitative metrics, as well as by using real patient CBCT scans for a qualitative evaluation by clinical experts. Results: The presented novel approach is able to generalize to unseen data and yields significant reductions in motion induced artifacts as well as improvements in image quality compared with existing state-of-the-art CBCT reconstruction algorithms (up to +6.3 dB and +0.19 improvements in peak signal-to-noise ratio, PSNR, and structural similarity index measure, SSIM, respectively), as evidenced by validation with an unseen test dataset, and confirmed by a clinical evaluation on real patient scans (up to 74% preference for motion artifact reduction over standard reconstruction). Conclusions: For the first time, it is demonstrated, also by means of clinical evaluation, that inserting deep neural networks as pre- and post-processing plugins in the existing 3D CBCT reconstruction and trained end-to-end yield significant improvements in image quality and reduction of motion artifacts.
@article{dir3ct, author = {Amirian, Mohammadreza and Montoya-Zegarra, Javier A. and Herzig, Ivo and Hotz, Peter Eggenberger and Lichtensteiger, Lukas and Morf, Marco and Z\"ust, Alexander and Paysan, Pascal and Peterlik, Igor and Scheib, Stefan and F\"uchslin, Rudolf Marcel and Stadelmann, Thilo and Schilling, Frank-Peter}, journal = {Med. Phys.}, title = {{Mitigation of motion-induced artefacts in Cone Beam Computed Tomography using Deep Convolutional Neural Networks}}, year = {2023}, number = {10}, pages = {6228-6242}, volume = {50}, doi = {10.1002/mp.16405}, modificationdate = {2024-02-03T16:37:27} }
certAInty: a certification scheme for AI systems

Joanna Weng, Monika Reif, Ricardo Chavarriaga, and Frank-Peter Schilling

In Poster presented at ZHAW Datalab Symposium, Winterthur, Switzerland, Feb 2023

DOI File
Deep learning the SKA: the Square Kilometer Array project

Philipp Denzel, Elena Gavagnin, and Frank-Peter Schilling

In Poster presented at ZHAW Datalab Symposium, Winterthur, Switzerland, Feb 2023

DOI File

2022

AoDS

Foundations of Data Science: A Comprehensive Overview Formed at the 1st International Symposium on the Science of Data Science

Frank-Peter Schilling, Dandolo Flumini, Rudolf M. Füchslin, Elena Gavagnin, and 3 more authors

Archives of Data Science, Series A, Feb 2022

Bib DOI File

@article{ISSDS21,
  author = {Schilling, Frank-Peter and Flumini, Dandolo and F{\"u}chslin, Rudolf M. and Gavagnin, Elena and Geller, Armando and Quarteroni, Silvia and Stadelmann, Thilo},
  title = {{Foundations of Data Science: A Comprehensive Overview Formed at the 1st International Symposium on the Science of Data Science}},
  journal = {Archives of Data Science, Series A},
  year = {2022},
  volume = {8},
  number = {2},
  pages = {1 -- 20},
  doi = {10.5445/IR/1000146422},
}

Deep Learning-Based Simultaneous Multi-Phase Deformable Image Registration of Sparse 4D-CBCT

Ivo Herzig, Pascal Paysan, Stefan Scheib, Frank-Peter Schilling, and 6 more authors

In Proceedings of the American Association of Physics in Medicine Annual Meeting (AAPM 2022), Feb 2022

Washington, DC, USA, July 2022

DOI File
Advances in Deep Neural Networks for Visual Pattern Recognition

Feb 2022

Special issue of J. Imaging (ISSN 2313-433X)

URL

2021

IEEE

A Survey of Un-, Weakly-, and Semi-Supervised Learning Methods for Noisy, Missing and Partial Labels in Industrial Vision Applications

Niclas Simmler, Pascal Sager, Philipp Andermatt, Ricardo Chavarriaga, and 3 more authors

In 8th Swiss Conference on Data Science (SDS), Feb 2021

Bib DOI File

@inproceedings{sds2021,
  author = {Simmler, Niclas and Sager, Pascal and Andermatt, Philipp and Chavarriaga, Ricardo and Schilling, Frank-Peter and Rosenthal, Matthias and Stadelmann, Thilo},
  booktitle = {8th Swiss Conference on Data Science (SDS)},
  title = {A Survey of Un-, Weakly-, and Semi-Supervised Learning Methods for Noisy, Missing and Partial Labels in Industrial Vision Applications},
  year = {2021},
  volume = {},
  number = {},
  pages = {26-31},
  doi = {10.1109/SDS51136.2021.00012},
}

2020

Artificial Neural Networks in Pattern Recognition

Feb 2020

Special issue of Computers (ISSN 2073-431X)

URL

Design Patterns for Resource-Constrained Automated Deep-Learning Methods

Lukas Tuggener, Mohammadreza Amirian, Fernando Benites, Pius Däniken, and 3 more authors

AI, Feb 2020

Bib DOI File

@article{autodl,
  author = {Tuggener, Lukas and Amirian, Mohammadreza and Benites, Fernando and von D{\"a}niken, Pius and Gupta, Prakhar and Schilling, Frank-Peter and Stadelmann, Thilo},
  title = {{Design Patterns for Resource-Constrained Automated Deep-Learning Methods}},
  journal = {AI},
  year = {2020},
  volume = {1},
  number = {4},
  pages = {510--538},
  doi = {10.3390/ai1040031},
}

Springer

Artificial neural networks in pattern recognition : Proceedings of the 9th IAPR TC3 workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020

Feb 2020

Bib DOI

@proceedings{annpr2020proc,
  title = {{Artificial neural networks in pattern recognition : Proceedings of the 9th IAPR TC3 workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020}},
  year = {2020},
  editor = {Schilling, Frank-Peter and Stadelmann, Thilo},
  volume = {Lecture Notes in Computer Science},
  number = {12294},
  publisher = {Springer},
  doi = {10.1007/978-3-030-58309-5},
}

Two to trust: AutoML for safe modelling and interpretable deep learning for robustness

Mohammadreza Amirian, Lukas Tuggener, Ricardo Chavarriaga, Yvan Putra Satyawan, and 3 more authors

Proc. of the 1st TAILOR Workshop on Trustworthy AI at ECAI 2020, Feb 2020

DOI File

2019

Efficient deep CNNs for cross-modal automated computer vision under time and space constraints

Mohammadreza Amirian, Katharina Rombach, Lukas Tuggener, Frank-Peter Schilling, and 1 more author

Proc. of ECML-PKDD 2019, Würzburg, Feb 2019

DOI File
Deep Learning in medizinischer Diagnostik und Qualitäts-kontrolle

Frank-Peter Schilling, and Thilo Stadelmann

Netzwoche, Special Issue: IT for Health, Feb 2019

DOI File

2017

Measurement of the mass difference between top quark and antiquark in pp collisions at \sqrts = 8 TeV

Serguei Chatrchyan, and others

Phys. Lett. B, Feb 2017

DOI File arXiv

2014

Nature Phys.

Evidence for the direct decay of the 125 GeV Higgs boson to fermions

Serguei Chatrchyan, and others

Nature Phys., Feb 2014

Bib DOI File arXiv

@article{higgsfermions,
  author = {Chatrchyan, Serguei and others},
  journal = {Nature Phys.},
  title = {{Evidence for the direct decay of the 125 GeV Higgs boson to fermions}},
  year = {2014},
  pages = {557},
  volume = {10},
  archiveprefix = {arXiv},
  collaboration = {CMS},
  creationdate = {2023-01-28T18:10:22},
  doi = {10.1038/nphys3005},
  eprint = {1401.6527},
  modificationdate = {2023-01-28T18:10:22},
  primaryclass = {hep-ex},
  reportnumber = {CMS-HIG-13-033, CERN-PH-EP-2014-004},
}

Phys. Rev.

Search for the standard model Higgs boson produced in association with a W or a Z boson and decaying to bottom quarks

Serguei Chatrchyan, and others

Phys. Rev., Feb 2014

Bib DOI File arXiv

@article{hbbpaper,
  author = {Chatrchyan, Serguei and others},
  journal = {Phys. Rev.},
  title = {{S}earch for the standard model {H}iggs boson produced in association with a {W} or a {Z} boson and decaying to bottom quarks},
  year = {2014},
  pages = {012003},
  volume = {D89},
  archiveprefix = {arXiv},
  collaboration = {CMS},
  creationdate = {2023-01-28T18:10:22},
  doi = {10.1103/PhysRevD.89.012003},
  eprint = {1310.3687},
  modificationdate = {2023-01-28T18:10:22},
  primaryclass = {hep-ex},
  reportnumber = {CMS-HIG-13-012, CERN-PH-EP-2013-188},
  timestamp = {2013.09.17}
}

2013

JHEP

Observation of a new boson with mass near 125 GeV in pp collisions at \sqrts = 7 and 8 TeV

Serguei Chatrchyan, and others

JHEP, Feb 2013

Bib DOI File arXiv

@article{chatrchyan:2013lba,
  author = {Chatrchyan, Serguei and others},
  journal = {JHEP},
  title = {{Observation of a new boson with mass near 125 GeV in pp collisions at $\sqrt{s}$ = 7 and 8 TeV}},
  year = {2013},
  pages = {081},
  volume = {1306},
  archiveprefix = {arXiv},
  collaboration = {CMS},
  creationdate = {2023-01-28T18:10:22},
  doi = {10.1007/JHEP06(2013)081},
  eprint = {1303.4571},
  modificationdate = {2023-01-28T18:10:22},
  primaryclass = {hep-ex},
  reportnumber = {CMS-HIG-12-036, CERN-PH-EP-2013-035}
}

Measurements of the Top Quark Pair-Production Cross Section

Frank-Peter Schilling

In 23rd Hadron Collider Physics Symposium, Kyoto, Japan, Feb 2013

DOI File arXiv
Search for the standard model Higgs boson produced in association with W or Z bosons, and decaying to bottom quarks

CMS Collaboration

Feb 2013

URL File

2012

Science

A New Boson with a Mass of 125 GeV Observed with the CMS Experiment at the Large Hadron Collider

Serguei Chatrchyan, and others

Science, Feb 2012

Bib DOI File

@article{science-higgs,
  author = {Chatrchyan, Serguei and others},
  journal = {Science},
  title = {{A New Boson with a Mass of 125 GeV Observed with the CMS Experiment at the Large Hadron Collider}},
  year = {2012},
  pages = {1569},
  volume = {338},
  collaboration = {CMS},
  creationdate = {2023-01-28T18:10:22},
  doi = {10.1126/science.1230816},
  modificationdate = {2023-01-28T18:10:22},
  timestamp = {2013.02.12},
}

Higgs
Discovery

Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC

Serguei Chatrchyan, and others

Phys.Lett., Feb 2012

Bib DOI File arXiv

@article{cms:2012gu,
  author = {Chatrchyan, Serguei and others},
  journal = {Phys.Lett.},
  title = {{Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC}},
  year = {2012},
  pages = {30-61},
  volume = {B716},
  archiveprefix = {arXiv},
  collaboration = {CMS},
  creationdate = {2023-01-28T18:10:22},
  doi = {10.1016/j.physletb.2012.08.021},
  eprint = {1207.7235},
  modificationdate = {2023-01-28T18:10:22},
  primaryclass = {hep-ex},
  reportnumber = {CMS-HIG-12-028, CERN-PH-EP-2012-220},
  timestamp = {2013.02.20},
}

Top Quark
Review

Top Quark Physics at the LHC: A Review of the First Two Years

F.-P. Schilling

Int. J. Mod. Phys., Feb 2012

Bib DOI File arXiv

@article{topreview,
  author = {Schilling, F.-P.},
  journal = {Int. J. Mod. Phys.},
  title = {{T}op {Q}uark {P}hysics at the {LHC}: {A} {R}eview of the {F}irst {T}wo {Y}ears},
  year = {2012},
  number = {17},
  pages = {1230016},
  volume = {A27},
  archiveprefix = {arXiv},
  doi = {10.1142/s0217751x12300165},
  eprint = {1206.4484},
  primaryclass = {hep-ex},
  timestamp = {2012.06.21},
}

Measurement of the single-top-quark t-channel cross section in pp collisions at \sqrts=7 TeV

Serguei Chatrchyan, and others

JHEP, Feb 2012

DOI File arXiv
Inclusive and differential measurements of the t \bart charge asymmetry in proton-proton collisions at 7 TeV

Serguei Chatrchyan, and others

Phys.Lett., Feb 2012

DOI File arXiv
Measurement of the charge asymmetry in top-quark pair production in proton-proton collisions at sqrt(s) = 7 TeV

Serguei Chatrchyan, and others

Phys.Lett., Feb 2012

DOI File arXiv
Search for the standard model Higgs boson produced in association with W or Z bosons, and decaying to bottom quarks

CMS Collaboration

Feb 2012

URL File

2011

Measurement of the t\bart Production Cross Section in pp Collisions at 7 TeV in Lepton + Jets Events Using b-quark Jet Identification

Serguei Chatrchyan, and others

Phys.Rev., Feb 2011

DOI File arXiv
Measurement of the t-channel single top quark production cross section in pp collisions at sqrt(s) = 7 TeV

Serguei Chatrchyan, and others

Phys.Rev.Lett., Feb 2011

DOI File arXiv
Measurement of the t t-bar production cross section and the top quark mass in the dilepton channel in pp collisions at sqrt(s) =7 TeV

Serguei Chatrchyan, and others

JHEP, Feb 2011

DOI File arXiv
Measurement of the Top-antitop Production Cross Section in pp Collisions at sqrt(s)=7 TeV using the Kinematic Properties of Events with Leptons and Jets

Serguei Chatrchyan, and others

Eur. Phys. J., Feb 2011

DOI File arXiv
First Measurement of the Cross Section for Top-Quark Pair Production in Proton-Proton Collisions at \sqrts=7 TeV

V. Khachatryan, and others

Phys.Lett., Feb 2011

DOI File arXiv
Combination of top pair production cross sections in pp collisions at 7 TeV and comparisons with theory

CMS Collaboration

Feb 2011

URL File

2010

Alignment of the CMS Silicon Tracker during Commissioning with Cosmic Rays

S Chatrchyan, and others

JINST, Feb 2010

DOI File arXiv
Top Quark Studies with the first CMS Data

Frank-Peter Schilling

In 21st Hadron Collider Physics Symposium, Toronto, Canada, Feb 2010

DOI File arXiv
Selection of Top-Like Events in the Dilepton and Lepton-plus-Jets Channels in Early 7 TeV Data

CMS Collaboration

Feb 2010

URL File

2009

Alignment of the CMS Silicon Strip Tracker during standalone Commissioning

S Chatrchyan, and others

JINST, Feb 2009

DOI File arXiv
Common Ntuple Output format for NLO Calculations

J. Campbell, J. Huston, P. Nadolsky, Frank-Peter Schilling, and 2 more authors

In 9th Workshop on Physics at TeV Colliders, Les Houches, France, Feb 2009

DOI File arXiv
Algorithms for b Jet Identification in CMS

CMS Collaboration

Feb 2009

URL File
Plans for an early Measurement of the t\bart Cross Section in the Electron-plus-Jets Channel at \sqrts = 10 TeV

CMS Collaboration

Feb 2009

URL File
Prospects for the first Measurement of the t\bart Cross Section in the Muon-plus-Jets Channel at \sqrts = 10 TeV with the CMS Detector

CMS Collaboration

Feb 2009

URL File

2008

The CMS tracker operation and performance at the Magnet Test and Cosmic Challenge

W. Adam, and others

JINST, Feb 2008

DOI File
The CMS experiment at the CERN LHC

R. Adolphi, and others

JINST, Feb 2008

DOI File
QCD and Top Quark Physics at the LHC

Frank-Peter Schilling

In 4th Intl. Conference on Physics at the LHC, Split, Croatia, Feb 2008

DOI File arXiv
Observability of Top Quark Pair Production in the Semileptonic Muon Channel with the first 10/pb of CMS Data

CMS Collaboration

Feb 2008

URL File
Measurement of the Top Quark Pair Production Cross Section with L=100/pb in Dileptonic Final States using the CMS Detector

CMS Collaboration

Feb 2008

URL File
Comprehensive set of misalignment scenarios for the CMS tracker

T. Lampen, N. De Filippis, F.-P. Schilling, A. Schmidt, and 1 more author

Feb 2008

URL File
Impact of Tracker Misalignment on the CMS b-Tagging Performance

CMS Collaboration

Feb 2008

URL File

2007

CMS technical design report, volume II: Physics performance

G.L. Bayatian, and others

J. Phys., Feb 2007

DOI
Early Electroweak and Top Quark Physics with CMS

Frank-Peter Schilling

In 15th Intl. Workshop on Deep-Inelastic Scattering and Related Subjects (DIS2007), Munich, Germany, Feb 2007

DOI File arXiv
Track Based Alignment in CMS

Frank-Peter Schilling

In 1st LHC Detector Alignment Workshop, Geneva, Switzerland, Feb 2007

DOI File arXiv
Introduction to the CMS contribution

P. Arce, O. Buchmuller, F. P. Schilling, I. Vila, and 1 more author

In 1st LHC Detector Alignment Workshop, Geneva, Switzerland, Feb 2007

DOI File
Status and commissioning of the CMS experiment

O. Buchmuller, and F. P. Schilling

In BEAUTY 2006, Oxford, UK, Feb 2007

DOI File arXiv
CMS Computing, Software and Analysis Challenge in 2006 (CSA06) Summary

CMS Collaboration

Feb 2007

URL File

2006

Track-based alignment of composite detector structures

V. Karimaki, T. Lampen, and F.-P. Schilling

IEEE Trans. Nucl. Sci., Feb 2006

DOI File
Measurement and QCD analysis of the diffractive deep- inelastic scattering cross-section at HERA

A. Aktas, and others

Eur. Phys. J., Feb 2006

DOI File arXiv
Diffractive deep-inelastic scattering with a leading proton at HERA

A. Aktas, and others

Eur. Phys. J., Feb 2006

DOI File arXiv
Track reconstruction and alignment with the CMS silicon tracker

F.-P. Schilling

In 33rd Intl. Conference on High Energy Physics (ICHEP 2006), Moscow, Russia, Feb 2006

DOI File arXiv
Impact of CMS silicon tracker misalignment on track and vertex reconstruction

L. Barbone, and others

In Workshop on Tracking in High Multiplicity Environments (TIME 2005), Zurich, Switzerland, Feb 2006

DOI File
Diffractive DIS cross sections and parton distributions

F.-P. Schilling

In 33rd Intl. Conference on High Energy Physics (ICHEP 2006), Moscow, Russia, Feb 2006

DOI File arXiv
Prospects for measuring B_s →μμwith the CMS detector

Frank-Peter Schilling

In 10th Intl. Conference on B Physics at Hadron Machines (BEAUTY 2005), Assisi, Italy, Feb 2006

DOI File arXiv
Prospects for diffractive and forward physics at the LHC

M. Albrow, and others

Feb 2006

URL File
CMS physics: Technical design report, Vol. 1: Software and Detector Performance

G. L. Bayatian, and others

Feb 2006

URL File
Impact of CMS silicon tracker misalignment on track and vertex reconstruction

P. Vanlaer, and others

Feb 2006

URL File
Fitting of event topologies with external kinematic constraints in CMS

J. D’Hondt, and others

Feb 2006

URL File
The HIP algorithm for track based alignment and its application to the CMS pixel detector

V. Karimaki, T. Lampen, and F.-P. Schilling

Feb 2006

URL File

2005

DPDF: A Library for Diffractive Parton Distributions

Frank-Peter Schilling

In HERA and the LHC: A Workshop on the Implications of HERA for LHC Physics, CERN and DESY, 2004-2005, Feb 2005

DOI File arXiv
HERA diffractive structure function data and parton distributions

Paul R. Newman, and F.-P. Schilling

In HERA and the LHC: A Workshop on the Implications of HERA for LHC Physics, CERN and DESY, 2004-2005, Feb 2005

DOI File arXiv
HERA diffractive structure function data and parton distributions

Paul Laycock, P. Newman, and F. P. Schilling

In 13th Intl. Workshop on Deep Inelastic Scattering (DIS 2005), Madison, USA, Feb 2005

DOI File

2004

Diffractive final states with the H1 detector at HERA

Frank-Peter Schilling

In Intl. Europhysics Conference on High-Energy Physics (EPS-HEP 2003), Aachen, Germany, Feb 2004

DOI File arXiv
Summary of working group B: Diffraction and vector mesons

Alessia Bruni, Markus Diehl, and Frank-Peter Schilling

In 12th Intl. Workshop on Deep Inelastic Scattering (DIS 2004), Slovakia (DESY-04-201), Feb 2004

DOI File arXiv
Diffractive D* Meson Production in Deep Inelastic ep Collisions at HERA

H1 Collaboration

Feb 2004

URL File
Dijets in Diffractive Photoproduction and Deep-Inelastic Scattering at HERA

H1 Collaboration

Feb 2004

URL File
Measurement of the Inclusive Cross Section for Diffractive Deep Inelastic Scattering at High Q2

H1 Collaboration

Feb 2004

URL File

2003

Measurement of inclusive jet cross-sections in photoproduction at HERA

C. Adloff, and others

Eur. Phys. J., Feb 2003

DOI File arXiv
Diffractive photoproduction of J/ψmesons with large momentum transfer at HERA

A. Aktas, and others

Phys. Lett., Feb 2003

DOI File arXiv
Inclusive diffraction at HERA

F.-P. Schilling

In 31st Intl. Conference on High Energy Physics (ICHEP 2002), Amsterdam, The Netherlands, Feb 2003

DOI File arXiv
Electron deuteron scattering with HERA, a letter of intent for an experimental programme with the H1 detector

T. Alexopoulos, and others

Feb 2003

URL File
Comparison at NLO between Predictions from QCD Fits to F2D and and Diffractive Final State Observables at HERA

H1 Collaboration

Feb 2003

URL File
Dijets in Diffractive Photoproduction at HERA

H1 Collaboration

Feb 2003

URL File

2002

Search for odderon-induced contributions to exclusive pi0 photoproduction at HERA

C. Adloff, and others

Phys. Lett., Feb 2002

DOI File arXiv
A measurement of the t dependence of the helicity structure of diffractive rho meson electroproduction at HERA

C. Adloff, and others

Phys. Lett., Feb 2002

DOI File arXiv
Energy flow and rapidity gaps between jets in photoproduction at HERA

C. Adloff, and others

Eur. Phys. J., Feb 2002

DOI File arXiv
NLO QCD fit to H1 diffractive DIS data

Frank-Peter Schilling

In 10th Intl. Workshop on Deep Inelastic Scattering (DIS 2002), Cracow, Poland, Feb 2002

URL File arXiv
Diffractive jet production in DIS: Testing QCD factorisation

F.-P. Schilling

In 9th Intl. Workshop on Deep Inelastic Scattering (DIS 2001), Bologna, Italy, Feb 2002

DOI File arXiv
Measurement and NLO DGLAP QCD Interpretation of Diffractive Deep-Inelastic Scattering at HERA

H1 Collaboration

Feb 2002

URL File
Measurement of the Diffractive DIS Cross Section at low Q2

H1 Collaboration

Feb 2002

URL File

2001

Diffractive jet production in deep inelastic e^+ p collisions at HERA

C. Adloff, and others

Eur. Phys. J., Feb 2001

DOI File arXiv
Hard Diffraction: Results from H1 at HERA

Frank-Peter Schilling

In Riken BNL Research Center Workshop (Vol. 34): High Energy QCD - Beyond the Pomeron, Upton, New York, USA, BNL-52641, Feb 2001

DOI File
Measurement of the Diffractive Structure Function F2D(3)(beta,Q2,xpom) at HERA

H1 Collaboration

Feb 2001

URL File
Diffractive Jet Production in Deep-Inelastic e+p Collisions at HERA

F.-P. Schilling

University of Heidelberg, Feb 2001

DESY-THESIS-2001-010

DOI URL File

2000

Diffractive dijet and 3-jet electroproduction at HERA

F.-P. Schilling

In 8th Intl. Workshop on Deep Inelastic Scattering (DIS 2000), Liverpool, UK, Feb 2000

DOI File arXiv
Diffractive Jet-Production in Deep-Inelastic e+p Collisions at HERA

H1 Collaboration

Feb 2000

URL File

1999

Diffractive dijet production at HERA

F.-P. Schilling

In 7th Intl. Workshop on Deep Inelastic Scattering (DIS 1999), Zeuthen, Germany, Feb 1999

DOI File
Diffractive Dijet Electroproduction at HERA

H1 Collaboration

Feb 1999

URL File

1998

Untersuchung von 2-Jet-Ereignissen in der diffraktiven tiefinelastischen Streuung mit dem H1-Detektor

F.-P. Schilling

University of Heidelberg, Feb 1998

H1TH-132

URL File