Explore the words cloud of the ExCAPE project. It provides you a very rough idea of what is the project "ExCAPE" about.
The following table provides information about the project.
Coordinator |
INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM
Organization address contact info |
Coordinator Country | Belgium [BE] |
Project website | http://excape-h2020.eu/ |
Total cost | 3˙910˙140 € |
EC max contribution | 3˙910˙140 € (100%) |
Programme |
1. H2020-EU.1.2.2. (FET Proactive) |
Code Call | H2020-FETHPC-2014 |
Funding Scheme | RIA |
Starting year | 2015 |
Duration (year-month-day) | from 2015-09-01 to 2018-08-31 |
Take a look of project's partnership.
# | ||||
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1 | INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM | BE (LEUVEN) | coordinator | 873˙146.00 |
2 | VYSOKA SKOLA BANSKA - TECHNICKA UNIVERZITA OSTRAVA | CZ (OSTRAVA PORUBA) | participant | 532˙500.00 |
3 | INTEL CORPORATION | BE (KONTICH) | participant | 507˙500.00 |
4 | JANSSEN CILAG SA | ES (Madrid) | participant | 448˙707.00 |
5 | ASTRAZENECA AB | SE (SODERTAELJE) | participant | 403˙125.00 |
6 | UNIVERSITAT LINZ | AT (LINZ) | participant | 371˙623.00 |
7 | ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE | UK (EGHAM) | participant | 369˙943.00 |
8 | AALTO KORKEAKOULUSAATIO SR | FI (ESPOO) | participant | 283˙593.00 |
9 | IDEACONSULT LIMITED LIABILITY COMPANY | BG (SOFIA) | participant | 120˙000.00 |
Scalable machine learning of complex models on extreme data will be an important industrial application of exascale computers. In this project, we take the example of predicting compound bioactivity for the pharmaceutical industry, an important sector for Europe for employment, income, and solving the problems of an ageing society. Small scale approaches to machine learning have already been trialed and show great promise to reduce empirical testing costs by acting as a virtual screen to filter out tests unlikely to work. However, it is not yet possible to use all available data to make the best possible models, as algorithms (and their implementations) capable of learning the best models do not scale to such sizes and heterogeneity of input data. There are also further challenges including imbalanced data, confidence estimation, data standards model quality and feature diversity.
The ExCAPE project aims to solve these problems by producing state of the art scalable algorithms and implementations thereof suitable for running on future Exascale machines. These approaches will scale programs for complex pharmaceutical workloads to input data sets at industry scale. The programs will be targeted at exascale platforms by using a mix of HPC programming techniques, advanced platform simulation for tuning and and suitable accelerators.
Final simulation and scalability report (4 and 2) | Documents, reports | 2019-07-25 13:11:11 |
Development report | Documents, reports | 2019-07-25 13:11:12 |
Report + Code 6 | Documents, reports | 2019-07-25 13:11:12 |
Metamodel report | Documents, reports | 2019-07-25 13:11:11 |
Simulation report 2 | Documents, reports | 2019-07-25 13:11:11 |
Tox | Other | 2019-07-25 13:11:11 |
Simulation Report 1 | Documents, reports | 2019-07-25 13:11:11 |
WebData | Other | 2019-07-25 13:11:12 |
Workflows report | Documents, reports | 2019-07-25 13:11:11 |
Report + Code 4 | Other | 2019-07-25 13:11:12 |
Factsheet 1 | Documents, reports | 2019-07-25 13:11:11 |
PublicBio | Other | 2019-07-25 13:11:11 |
PublicCancer | Other | 2019-07-25 13:11:11 |
Workshop 2 | Demonstrators, pilots, prototypes | 2019-07-25 13:11:12 |
Website | Websites, patent fillings, videos etc. | 2019-07-25 13:11:11 |
Factsheet 2 | Documents, reports | 2019-07-25 13:11:12 |
Scalability report 1 | Documents, reports | 2019-07-25 13:11:11 |
Challenge report | Documents, reports | 2019-07-25 13:11:11 |
Social | Websites, patent fillings, videos etc. | 2019-07-25 13:11:12 |
Criteria report | Documents, reports | 2019-07-25 13:11:11 |
Simulation report 3 | Documents, reports | 2019-07-25 13:11:11 |
Take a look to the deliverables list in detail: detailed list of ExCAPE deliverables.
year | authors and title | journal | last update |
---|---|---|---|
2015 |
Djork-Arne Clevert, Thomas Unterthiner, Sepp Hochreiter Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) published pages: 1-14, ISSN: , DOI: |
CoRR abs/1511.07289 | 2019-07-25 |
2016 |
Vladimir Vovk, Dusko Pavlovic Universal Probability-Free Conformal Prediction published pages: 40-47, ISSN: , DOI: 10.1007/978-3-319-33395-3_3 |
COPA 2016: Conformal and Probabilistic Prediction with Applications | 2019-07-25 |
2016 |
Vladimir Vovk, Valentina Fedorova, Ilia Nouretdinov, Alexander Gammerman Criteria of Efficiency for Conformal Prediction published pages: 23-39, ISSN: , DOI: 10.1007/978-3-319-33395-3_2 |
COPA 2016: Conformal and Probabilistic Prediction with Applications | 2019-07-25 |
2015 |
Valentina Fedorova, Alex Gammerman, Ilia Nouretdinov, Vladimir Vovk Hypergraphical Conformal Predictors published pages: 1560003, ISSN: 0218-2130, DOI: 10.1142/S0218213015600039 |
International Journal on Artificial Intelligence Tools 24/06 | 2019-07-25 |
2017 |
Jiangming Sun, Nina Jeliazkova, Vladimir Chupakin, Jose-Felipe Golib-Dzib, Ola Engkvist, Lars Carlsson, Jörg Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay Kochev, Thomas J. Ashby, Hongming Chen ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics published pages: , ISSN: 1758-2946, DOI: 10.1186/s13321-017-0203-5 |
Journal of Cheminformatics 9/1 | 2019-07-25 |
2016 |
Michael Treml, José Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Bernhard Nessler, Sepp Hochreiter Speeding up Semantic Segmentation for Autonomous Driving published pages: 1-7, ISSN: , DOI: |
OpenReview | 2019-07-25 |
2016 |
Paolo Toccaceli, Ilia Nouretdinov, Alexander Gammerman Conformal Predictors for Compound Activity Prediction published pages: 51-66, ISSN: , DOI: 10.1007/978-3-319-33395-3_4 |
COPA 2016: Conformal and Probabilistic Prediction with Applications | 2019-07-25 |
2017 |
Ilia Nouretdinov Validity and efficiency of conformal anomaly detection on big distributed data published pages: 254-267, ISSN: 2415-6698, DOI: 10.25046/aj020335 |
Advances in Science, Technology and Engineering Systems Journal 2/3 | 2019-07-25 |
2017 |
V. Vovk Purely pathwise probability-free Ito integral published pages: , ISSN: 1027-4634, DOI: 10.15330/ms.46.1.96-110 |
Matematychni Studii 46/1 | 2019-07-25 |
2017 |
Imen Chakroun, Tom Haber, Thomas J. Ashby SW-SGD: The Sliding Window Stochastic Gradient Descent Algorithm published pages: 2318-2322, ISSN: 1877-0509, DOI: 10.1016/j.procs.2017.05.082 |
Procedia Computer Science 108 | 2019-07-25 |
2017 |
Balazs Nemeth, Tom Haber, Thomas J. Ashby, Wim Lamotte Improving Operational Intensity in Data Bound Markov Chain Monte Carlo published pages: 2348-2352, ISSN: 1877-0509, DOI: 10.1016/j.procs.2017.05.024 |
Procedia Computer Science 108 | 2019-07-25 |
2018 |
Noé Sturm, Jiangming Sun, Yves Vandriessche, Andreas Mayr, Günter Klambauer, Lars-Anders Carlson, Ola Engkvist, Hongming Chen Application of Bioactivity Profile Based Fingerprints for Building Machine Learning Models published pages: , ISSN: 2573-2293, DOI: 10.26434/chemrxiv.6969584.v1 |
ChemRxiv | 2019-07-25 |
2017 |
Tom Vander Aa, Imen Chakroun, Tom Haber Distributed Bayesian Probabilistic Matrix Factorization published pages: 1030-1039, ISSN: 1877-0509, DOI: 10.1016/j.procs.2017.05.009 |
Procedia Computer Science 108 | 2019-07-25 |
2017 |
Paolo Toccaceli, Ilia Nouretdinov, Alexander Gammerman Conformal prediction of biological activity of chemical compounds published pages: 105-123, ISSN: 1012-2443, DOI: 10.1007/s10472-017-9556-8 |
Annals of Mathematics and Artificial Intelligence 81/1-2 | 2019-07-25 |
2017 |
Vladimir Vovk The role of measurability in game-theoretic probability published pages: 719-739, ISSN: 0949-2984, DOI: 10.1007/s00780-017-0336-4 |
Finance and Stochastics 21/3 | 2019-07-25 |
2018 |
Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Marvin Steijaert, Jörg K. Wegner, Hugo Ceulemans, Djork-Arné Clevert, Sepp Hochreiter Large-scale comparison of machine learning methods for drug target prediction on ChEMBL published pages: 5441-5451, ISSN: 2041-6520, DOI: 10.1039/c8sc00148k |
Chemical Science 9/24 | 2019-07-25 |
2018 |
Vladimir Vovk, Jieli Shen, Valery Manokhin, Min-ge Xie Nonparametric predictive distributions based on conformal prediction published pages: , ISSN: 0885-6125, DOI: 10.1007/s10994-018-5755-8 |
Machine Learning | 2019-07-25 |
2017 |
Gundula Povysil, Antigoni Tzika, Julia Vogt, Verena Haunschmid, Ludwine Messiaen, Johannes Zschocke, Günter Klambauer, Sepp Hochreiter, Katharina Wimmer panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics published pages: 889-897, ISSN: 1059-7794, DOI: 10.1002/humu.23237 |
Human Mutation 38/7 | 2019-07-25 |
2017 |
Vladimir Vovk, Ilia Nouretdinov, Valentina Fedorova, Ivan Petej, Alex Gammerman Criteria of efficiency for set-valued classification published pages: 21-46, ISSN: 1012-2443, DOI: 10.1007/s10472-017-9540-3 |
Annals of Mathematics and Artificial Intelligence 81/1-2 | 2019-07-25 |
2018 |
Alberto Scionti, Somnath Mazumdar, Antoni Portero Towards a Scalable Software Defined Network-on-Chip for Next Generation Cloud published pages: 2330, ISSN: 1424-8220, DOI: 10.3390/s18072330 |
Sensors 18/7 | 2019-07-25 |
2018 |
Paolo Toccaceli, Alexander Gammerman Combination of inductive mondrian conformal predictors published pages: , ISSN: 0885-6125, DOI: 10.1007/s10994-018-5754-9 |
Machine Learning | 2019-07-25 |
2017 |
Vladimir Vovk, Dusko Pavlovic Universal probability-free prediction published pages: 47-70, ISSN: 1012-2443, DOI: 10.1007/s10472-017-9547-9 |
Annals of Mathematics and Artificial Intelligence 81/1-2 | 2019-07-25 |
2018 |
Nikolay Kochev, Svetlana Avramova, Nina Jeliazkova Ambit-SMIRKS: a software module for reaction representation, reaction search and structure transformation published pages: , ISSN: 1758-2946, DOI: 10.1186/s13321-018-0295-6 |
Journal of Cheminformatics 10/1 | 2019-07-25 |
2017 |
Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski Exploratory Analysis of Multiple Data Sources with Group Factor published pages: 1-5, ISSN: 1533-7928, DOI: |
Journal of Machine Learning Research 18, 04-2017 | 2019-07-25 |
2017 |
Paolo Toccaceli, Alexander Gammerman Combination of Conformal Predictors for Classification published pages: 39-61, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research: The Sixth Workshop on Conformal and Probabilistic Prediction and Applications 60, 2017 | 2019-07-25 |
2018 |
Xiangju Qin, Paul Blomstedt, Samuel Kaski Large-scale probabilistic non-linear matrix factorization for drug discovery published pages: https://www.ijca, ISSN: , DOI: |
3rd International workshop on biomedical informatics with optimization and machine learning 15th April | 2019-07-25 |
2017 |
Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski Distributed Bayesian Matrix Factorization with Limited Communication published pages: , ISSN: , DOI: |
arXiv 02 March 2017 | 2019-07-25 |
2017 |
Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter Self-Normalizing Neural Networks published pages: 971--980, ISSN: , DOI: |
Advances in Neural Information Processing Systems 30 (NIPS 2017) 4.12-9.12.2017 | 2019-07-25 |
2018 |
Ilia Nouretdinov, Denis Volkhonskiy, Pitt Lim, Paolo Toccaceli, Alexander Gammerman Inductive Venn-Abers predictive distribution published pages: 15-36, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research: The Seventh Workshop on Conformal and Probabilistic Prediction and Applications 91, 2018 | 2019-07-25 |
2017 |
Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter Self-Normalizing Neural Networks published pages: , ISSN: , DOI: |
ArXiv 8.6.2017 | 2019-07-25 |
2017 |
Ilia Nouretdinov Improving Reliable Probabilistic Prediction by Using Additional Knowledge published pages: 193-200, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research: The Sixth Workshop on Conformal and Probabilistic Prediction and Applications 60, 2017 | 2019-07-25 |
2017 |
Tom Vander Aa, Tom Ashby, Yves Vandriessche, Vojtech Cima, Stanislav Böhm, Jan Martinovic Machine Learning for Chemogenomics on HPC in the ExCAPE Project published pages: 72 to 74, ISSN: 2308-3484, DOI: |
INFOCOMP17 June 25, 2017 | 2019-07-25 |
2018 |
Vladimir Vovk, Claus Bendtsen Conformal predictive decision making published pages: 52-62, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research: The Seventh Workshop on Conformal and Probabilistic Prediction and Applications 91, 2018 | 2019-07-25 |
2017 |
Denis Volkhonskiy, Evgeny Burnaev, Ilia Nouretdinov, Alexander Gammerman, Vladimir Vovk Inductive Conformal Martingales for Change-Point Detection published pages: 132-153, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research Proceedings: The Sixth Workshop on Conformal and Probabilistic Prediction and Applications 60, 2017 | 2019-07-25 |
2017 |
Ilia Nouretdinov Reverse Conformal Approach for On-line Experimental Design published pages: 185-192, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research: The Sixth Workshop on Conformal and Probabilistic Prediction and Applications 60, 2017 | 2019-07-25 |
2017 |
Vladimir Vovk, Jieli Shen, Valery Manokhin, Min-ge Xie Nonparametric predictive distributions based on conformal prediction published pages: 82-102, ISSN: 1938-7228, DOI: |
Proceedings of Machine Learning Research Proceedings: The Sixth Workshop on Conformal and Probabilistic Prediction and Applications 60, 2017 | 2019-07-25 |
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The information about "EXCAPE" are provided by the European Opendata Portal: CORDIS opendata.