CAI - Towards Exascale Computing Architecture and Its Prototype: Services and Infrastructure

Jan Meizner, Piotr Nowakowski, Jan Kapala, Patryk Wojtowicz, Marian Bubak, Viet Tran, Martin Bobák, Maximilian Höb; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - Processing Radio Astronomical Data Using the PROCESS Software Ecosystem

Souley Madougou, Hanno Spreeuw, Jason Maassen; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - Breast Histopathology with High-Performance Computing and Deep Learning

Mara Graziani, Ivan Eggel, François Deligand, Martin Bobák, Vincent Andrearczyk, Henning Müller; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - PROCESS Data Infrastructure and Data Services

Reginald Cushing, Onno Valkering, Adam Belloum, Souley Madougou, Jason Maassen, Martin Bobák, Ondrej Habala, Viet Tran, Jan Meizner, Piotr Nowakowski, Mara Graziani, Henning Müller; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - Cookery: A Framework for Creating Data Processing Pipeline Using Online Services

Mikołaj Baranowski, Adam Belloum, Reginald Cushing, Onno Valkering; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - Reference Exascale Architecture (Extended Version)

Martin Bobák, Ladislav Hluchý, Ondrej Habala, Viet Tran, Reginald Cushing, Onno Valkering, Adam Belloum, Mara Graziani, Henning Müller, Souley Madougou, Jason Maassen; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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CAI - Preface to the Special Issue on Providing Computing Solutions for Exascale Challenges

Dieter Kranzlmüller, Maximilian Höb; CAI (Computer and Informatics), Vol. 39, No 4, 2020

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Human-centric interpretability of deep learning for digital pathology

M. Graziani, conference at the SDP, Swiss Digital Pathology, Consortium (extract)

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Rocket: Efficient and Scalable All-Pairs Computations on Heterogeneous Platforms

S. Heldens, P. Hijma et al.; preprint at Arxiv (Cornell University): https://arxiv.org/abs/2008.01478

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Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning

M. Graziani, S. Otálora et al.; preprint at Arxiv (Cornell University): https://arxiv.org/abs/2008.01478

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Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging

M. Graziani, T. Lompech et al; at IMIMIC ’20 (https://imimic-workshop.com/)

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Fascinating research project (a look at PROCESS from inside)

A. M. Orosz; Lufthansa Systems,  2020 (internal corporate blog)

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Prepaid baggage sales will go through the roof

K. Lehman; Lufthansa Systems,  2020 (internal corporate blog)

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Concept attribution: Explaining CNN decisions to physicians

M. Graziani et al., Computers in Biology and Medicine,  2020

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The value of baggage: dynamic pricing methods for ancillaries

F. Berger; Lufthansa Systems,  2020 (at https://www.lhsystems.com/blogs)

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Enabling EASEY deployment of containerized applications for future HPC systems

M. Höb; D. Kranzlmüller, ICCS , 2020

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How should you interpret your deep learning model?

M. Graziani , medium.com,  2020

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The Landscape of Exascale Research: A Data-Driven Literature Analysis

S. Heldens, P.Hijma et al., At ACM Computing Surveys, March 2020. https://dl.acm.org/doi/abs/10.1145/3372390

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A hybrid HPC and Cloud platform for multidisciplinary scientific application

M. Bubak et al., Supercomputers Frontiers 2020, Warsaw, Poland (virtual), 2020

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A hybrid platform for exascale multidisciplinary scientific applications

J. Meizner et al., Supercomputers Frontiers 2020, Warsaw, Poland (virtual), 2020

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Interpreting Intentionally Flawed Models with Linear Probes

M. Graziani, H. Muller, V. Andrearczyk; 1st workshop on Statistical Deep Learning for Computer Vision,
Seoul, Korea, 2019

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Reduction of radio astronomical observations to sky maps as an Example of Exascale Data Service

Ladislav Hluchý, Jason Maassen, and Hanno Spreeuw; Parnum, the 13^th workshop in the series of the “Parallel Numerics” workshops;
Dubrovnik, Croatia, 2019

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Towards Exascale-ready Data Service Solutions

Maximilian Höb; EOSC Workshop, Helsinki, Finland 2019

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Reference exascale architecture

Martin Bobak, Ladislav Hluchy, Adam S. Z. Belloum, Reginald Cushing, Jan Meizner, Piotr Nowakowski, Viet Tran, Ondrej Habala, Jason Maassen, Balazs Somoskoi, Mara Graziani, Matti Heikkurinen, Maximilian Höb, Jan Schmidt; e-Science, San Diego, USA, 2019

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Reference exascale architecture

Adam S. Z. Belloum, Reginald Cushing, Jan Meizner, Piotr Nowakowski, Viet Tran, Ondrej Habala, Jason Maassen, Balázs Somoskoi, Mara Graziani, Matti Heikkurinen, Maximilian Hob and Jan Schmidt; e-Science, San Diego, USA, 2019

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Unlocking the LOFAR LTA

Hanno Spreeuw, Souley Madougou, Ronald van Haren, Berend Weel, Adam Belloum, Jason Maassen; e-Science, San Diego, USA, 2019

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Unlocking the LOFAR LTA

Hanno Spreeuw, Souley Madougou, Ronald van Haren, Berend Weel, Adam Belloum, Jason Maassen; e-Science, San Diego, USA, 2019

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Machine Learning in Medical Imaging

Martin Bobák, L. Hluchý, M. Graziani, H. Müller; International Conference on new research and development in technical and natural science, Radenci, Slovenia, 2019

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Anomaly Detection Method for Online Discussion

P. Krammer, O. Habala, J. Mojžiš, L. Hluchý, M. Jurkovič; The 14th International Conference on Future Networks and Communications (FNC), August 19-21, 2019, Halifax, Canada

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Visualizing and Interpreting Feature Reuse of Pretrained CNNs for Histopathology

M. Graziani, V. Andrearczy, H. Müller; Irish Machine Vision and Image Processing Conference, Dublin, Ireland, 2019

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Privacy-Preserving Record Linkage with Spark

O. Valkering, A. Belloum; EGI workshop; Amsterdam, The Netherlands, 2019

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Interpretability of Machine Learning Systems for Medical Imaging

Mara Graziani, HES-SO; Geneva, Switzerland, 2019

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In quest for reproducibility of medical simulations on e-infrastructures

Video at CompBioMed Containerisation Meeting. Marian Bubak, AGH/AGH-UST; Amsterdam, The Netherlands, March-2019

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Heterogeneous Exascale Computing

L. Hluchý et al.; International Conference on Intelligent Engineering Systems; Las Palmas, Spain, 2019

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Improved interpretability for computer-aided severity assessment of Retinopathy of Prematurity

M. Graziani et al.; SPIES Conference, San Diego, USA, 2018

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Validating Data Integrity With Blockchain

R. Kalis, A. Belloum

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A Resource Usage Prediction System Using Functional-link and Genetic Algorithm Neural Network for Multivariate Cloud Metrics

T. Nguyen, N. Tran, B. M. Nguyen, G. Nguyen; 2018 IEEE 11th International Conference on Service-Oriented Computing and Applications

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Regression Concept Vectors for explanations of Deep Learning

M. Graziani, SMLD 2018

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Platform-driven e-infrastructure Innovations

J. Meisner et al, 14th e-science

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From Scalable, Semantically-based Distributed Computing to Exascale Computing

Ladislav Hluchý; CGW workshop, Kraków, Poland, 2018

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Regression Concept Vectors for Bidirectional Explanations in Histopathology

M. Graziani, V. Andrearczyk, H. Muller

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Clustering analysis of online discussion participants

P. Krammer, M. Kvassay, J. Mojžiš, I. Budinská, L. Hluchý, M. Jurkovič; The 13th International Conference on Future Networks and Communications (FNC 2018)​

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Exascale Computing and Data Architectures for Brownfield Applications

M Bobak et al.; 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery

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Invited talk at the Cambridge Engineering Department

HES-SO, Jun-2018

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Research infrastructures and medical image analysis

H. Muller; SPDC, Geneva, Switzerland, Jun-2018

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Crawling and Analysis of Online Discussions in Major Slovak National Newspapers

J. Mojžiš, P. Krammer, M. Kvassay, I. Budinská, L. Hluchý, M. Jurkovič; 22nd IEEE International Conference on Intelligent Engineering Systems (INES 2018)

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Predicting the Probability of Exceeding Critical System Threholds

P. Krammer, M. Kvassay, L. Hluchý; CEUR Workshop Proceedings, Kyiv, Ukraine, 2018

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Use Case # 1: Exascale Learning on Medical Image Data

M. Graziani

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PROCESS project overview

HES-SO, Dec-2017

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New Method for Constructing a Visibility Graph-Network in 3D Space and a New Hybrid System of Modeling

M. Babič, L. Hluchy, P. Krammer, B. Matovič, R. Kumar, P. Kovač; Computing and Informatics, Vol. 36, 2017

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