Machine Learning

Mitarbeiter: Jörn Ostermann, Bodo Rosenhahn, Hanno Ackermann, Bastian Wandt, Maren Awiszus, Florian Kluger, Daniel Gritzner, Marius Lindauer, Theresa Eimer
Einleitung

Am Institut für Informationsverarbeitung (TNT) werden Methoden im breiten Feld des Machine Learning entwickelt und auf verschiedene Problemstellungen angewandt. Das Ziel ist es, automatisiert Wissen und semantische Zusammenhänge aus großen Datenmengen zu extrahieren. Diese Informationen sind für Anwendungen wie z.B. autonomes Fahren, Krebsdiagnose, Luftbildauswertung, Augmented Reality und Industrie 4.0 extrem wichtig.

 

Aktuelle Forschungsthemen

Autonomes Fahren:

Autonome Fahrzeuge erhöhen die Sicherheit aller Teilnehmer im Straßenverkehr, indem fehlbare menschliche Fahrer durch zuverlässige Algorithmen ersetzt werden. Dazu sind robuste Methoden zur semantischen Analyse der Fahrumgebung notwendig, auf deren Basis Gefahrensituationen erkannt und Entscheidungen getroffen werden. Mithilfe maschineller Lernverfahren entwickelt das TNT Algorithmen, welche Daten unterschiedlicher Sensoren – z.B. Kameras oder Lidar – analysieren, um sicheres autonomes Fahren zu ermöglichen.

Bildsynthese mit Neuronalen Netzen:

Mit gegeneinander arbeitenden Netzwerken, sogenannten Adversarial Neworks, ist es möglich, unterschiedliche Aufgaben wie die Generierung realistisch wirkender Bilder und den Informations-transfer zwischen unterschiedlichen Domänen und Sensoren zu bewerkstelligen. So kann beispielsweise die Auflösung eines Bildes erhöht oder fehlende bzw. verdeckte Bildbereiche rekonstruiert werden.

Einsatz von Low-Cost-Sensoren:

Teilnehmer im alltäglichen Straßenverkehr können mit Hilfe von Low-Cost-Sensoren in kurzer Zeit große Mengen interessanter Daten sammeln und zugänglich machen. Daraus werden mit grafischen Modellen und spezialisierten Neuronalen Netzen semantische Informationen extrahiert, wie z.B. Baustellen, welche die Bewegungsfreiheit einschränken, oder Stoßzeiten im Verkehr.

Videospiel AI:

Videospiele stellen vielfältige, aber gleichzeitig gut kontrollierbare Umgebungen zur Erforschung von Algorithmen zur Entscheidungsplanung dar. Beispielsweise werden mit Reinforcement Learning intelligente Agenten für Videospiele entwickelt, welche die gleichen Informationen und Möglichkeiten wie echte Spieler haben.

Luftbildauswertung:

Aus Luftbildern lassen sich viele interessante Informationen extrahieren, z.B. aktuelle Karten, Städtewachstum über die Zeit, die Beurteilung von Verkehrsaufkommen oder der Auslastung von Parkplätzen. Das TNT setzt Deep Learning ein, um automatisch sowohl die Art der Nutzung von Flächen zu ermitteln, als auch Objekte in Luftbildern zu erkennen. EOT;

Verwendete Methoden

Neuronale Netze (CNNs, Autoencoder, RNNs, GANs, …) , Statistische Lernverfahren (Random Forest, Gaussian Mixture Models, Hidden Markov Models, …) , Bestärkendes Lernen (Q-Learning, MCTS, …)

 

 

  • Conference Contributions
    • Yuren Cong, Hanno Ackermann, Wentong Liao, Michael Ying Yang, Bodo Rosenhahn
      NODIS: Neural Ordinary Differential Scene Understanding
      European Conference on Computer Vision (ECCV), August 2020
    • He Sen, Liao Wentong, Hamed Rezazadegan Tavakoli, Michael Ying Yang, Bodo Rosenhahn, Nicolas Pugeault
      Image Captioning through Image Transformer
      Asian Conference on Computer Vision (ACCV), IEEE, Kyoto, November 2020
    • Andre Biedenkapp, H. Furkan Bozkurt, Theresa Eimer, Frank Hutter, Marius Lindauer
      Algorithm Control: Foundation of a New Meta-Algorithmic Framework
      Proceedings of the European Conference on Artificial Intelligence (ECAI), 2020
    • David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller, Marius Lindauer
      Learning Heuristic Selection with Dynamic Algorithm Configuration
      Proceedings of international workshop on Bridging the Gap Between AI Planning and Reinforcement Learning at ICAPS, June 2020
    • Theresa Eimer, Andre Biedenkapp, Frank Hutter, Marius Lindauer
      Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning
      Workshop on Inductive Biases, Invariances and Generalization in Reinforcement Learning (BIG@ICML'20), July 2020
    • Gresa Shala, Andre Biedenkapp, Noor Awad, Steven Adriaensen, Marius Lindauer, Frank Hutter
      Learning Step-Size Adaptation in CMA-ES
      Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature ({PPSN}'20), September 2020
    • Idoia Ochoa, Hongyi Li, Florian Baumgarte, Charles Hergenrother, Jan Voges, Mikel Hernaez
      AliCo: a new efficient representation for SAM files
      2019 Data Compression Conference (DCC), IEEE Computer Society Conference Publishing Services (CPS), pp. 93-102, Snowbird, UT (US), March 2019
    • Tom Paridaens, Jan Voges, Mikel Hernaez, Jan Fostier, Jörn Ostermann
      GABAC: an arithmetic coding solution for genomic data
      27th Conference on Intelligent Systems for Molecular Biology (ISMB) and 18th European Conference on Computational Biology (ECCB) 2019, International Society for Computational Biology (ISCB), Vol. 8, p. 1463 (poster), Basel (CH), July 2019
    • Jan Voges
      Optimization Strategy for MPEG-G Compliant Entropy Encoding
      Contributions 5th ITG/VDE Summer School Video Compression and Processing (SVCP), University of Konstanz, pp. 228-255, Konstanz (DE), June 2019, edited by Dietmar Saupe, André Kaup, Jens-Rainer Ohm
    • Brian E Bliss, Joshua M Allen, Saurabh Baheti, Matthew A Bockol, Shubham Chandak, Jaime Delgado, Jan Fostier, Josep L Gelpi, Steven N Hart, Mikel Hernaez Arrazola, Matthew E Hudson, Michael T Kalmbach, Eric W Klee, Liudmila S Mainzer, Fabian Müntefering, Daniel Naro, Idoia Ochoa-Alvarez, Jörn Ostermann, Tom Paridaens, Christian A Ross, Jan Voges, Eric D Wieben, Mingyu Yang, Tsachy Weissman, Mathieu Wiepert
      Genie: an MPEG-G conformant software to compress genomic data
      International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), p. (poster), Denver, CO (US), November 2019
    • Maximilian Benedikt Schier, Niclas Wüstenbecker
      Adversarial N-player Search using Locality for the Game of Battlesnake
      INFORMATIK 2019, September 2019
    • M. Lindauer and M. Feurer and K. Eggensperger and A. Biedenkapp and F. Hutter
      Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
      {IJCAI} 2019 {DSO} Workshop, August 2019
    • Jan Voges, Ali Fotouhi, Jörn Ostermann, M. Oguzhan Külekci
      A Two-Level Scheme for Quality Score Compression
      Proceedings of the 10th International Conference on Bioinformatics and Computational Biology (BICOB 2018), International Society for Computers and their Applications (ISCA), pp. 161-167, Las Vegas, NV (US), March 2018, edited by Hisham Al-Mubaid, Qin Ding, Oliver Eulenstein
    • Ana A Hernandez-Lopez, Jan Voges, Claudio Alberti, Marco Mattavelli, Jörn Ostermann
      Lossy Compression of Quality Scores in Differential Gene Expression: A First Assessment and Impact Analysis
      2018 Data Compression Conference (DCC), IEEE Computer Society Conference Publishing Services (CPS), pp. 167-176, Snowbird, UT (US), March 2018
    • Jan Voges
      MPEG-G: The Standard for Genomic Information Representation
      Proceedings of the 4th Summer School on Video Compression and Processing (SVCP) 2018, Leibniz Universität Hannover, Institut für Informationsverarbeitung, pp. 7-8, Hannover (DE), July 2018, edited by Jan Voges
    • Christoph Reinders, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
      Object Recognition from very few Training Examples for Enhancing Bicycle Maps
      2018 IEEE Intelligent Vehicles Symposium (IV), June 2018
    • M. Feurer and K. Eggensperger and S. Falkner and M. Lindauer and F. Hutter
      Practical Automated Machine Learning for the AutoML Challenge 2018
      ICML 2018 AutoML Workshop, July 2018
    • K. Eggensperger and M. Lindauer and F. Hutter
      Neural Networks for Predicting Algorithm Runtime Distributions
      Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18), pp. 1442-1448, July 2018
    • A. Biedenkapp and J. Marben and M. Lindauer and F. Hutter
      CAVE: Configuration Assessment, Visualization and Evaluation
      Proceedings of the International Conference on Learning and Intelligent Optimization (LION'18), June 2018
    • Wentong Liao, Chun Yang, Michael Ying Yang, Bodo Rosenhahn
      Security Event Recognition for Visual Surveillance
      ISPRS Annals of Photogrammetry, Remote Sensing \& Spatial Information Sciences, Vol. 4, June 2017
    • Ana A Hernandez-Lopez, Jan Voges, Claudio Alberti, Marco Mattavelli, Jörn Ostermann
      Differential Gene Expression with Lossy Compression of Quality Scores in RNA-Seq Data
      2017 Data Compression Conference (DCC), IEEE Computer Society Conference Publishing Services (CPS), p. 444 (poster), Snowbird, UT (US), April 2017
    • Jan Voges, Jörn Ostermann, Mikel Hernaez
      CALQ: compression of quality values of aligned sequencing data
      Joint 25th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 16th European Conference on Computational Biology (ECCB) 2017, International Society for Computational Biology (ISCB), Vol. 6, p. 1382 (poster), Prague (CZ), August 2017
    • Jan Voges, Jörn Ostermann
      MPEG-G: The Emerging Standard for Genomic Data
      Poster abstracts of the 25th German Conference on Bioinformatics, PeerJ, Vol. 5, p. 2 (poster), Tübingen (DE), September 2017
    • Florian Kluger, Hanno Ackermann, Michael Ying Yang, Bodo Rosenhahn
      Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection
      39th German Conference on Pattern Recognition, Springer Lecture Notes in Computer Science (LNCS), Basel, Switzerland, September 2017
    • Claudio Alberti, Noah Daniels, Mikel Hernaez, Jan Voges, Rachel L Goldfeder, Ana A Hernandez-Lopez, Marco Mattavelli, Bonnie Berger
      An Evaluation Framework for Lossy Compression of Genome Sequencing Quality Values
      2016 Data Compression Conference (DCC), IEEE Computer Society Conference Publishing Services (CPS), pp. 221-230, Snowbird, UT (US), April 2016
    • Jan Voges, Marco Munderloh, Jörn Ostermann
      Predictive Coding of Aligned Next-Generation Sequencing Data
      2016 Data Compression Conference (DCC), IEEE Computer Society Conference Publishing Services (CPS), pp. 241-250, Snowbird, UT (US), April 2016
    • Wentong Liao, Bodo Rosenhahn, Yang Michael
      Gaussian Process for Activity Modeling and Anomaly Detection
      International Society for Photogrammetry and Remote Sensing ISA workshop, La Grande Motte, France, September 2015
    • Wentong Liao, Yang Michael, Bodo Rosenhahn
      Video Event Recognition by Combining HDP and Gaussian Process
      IEEE International Conference on Computer Vision (ICCV) Workshop, pp. 19-27, Santiago, Chile, December 2015
    • Michael Ying Yang, Yu Qiang, Bodo Rosenhahn
      A global-to-local framework for infrared and visible image sequence registration
      IEEE Winter Conference on Applications of Computer Vision, accpeted for publication, January 2015
    • Michael Ying Yang
      A Generic Probabilistic Graphical Model for Region-based Scene Interpretation
      International Conference on Computer Vision Theory and Applications, accpeted for publication, March 2015
    • Florian Baumann, Liu Wei, Arne Ehlers, Bodo Rosenhahn
      Sequential Boosting for Learning a Random Forest Classifier
      IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Beach, HI, USA, January 2015
    • Florian Baumann, Karsten Vogt, Arne Ehlers, Bodo Rosenhahn
      Probabilistic Nodes for Modelling Classification Uncertainty for Random Forest
      14th IAPR International Conference on Machine Vision Applications (MVA), Tokio, Japan, May 2015
    • Florian Baumann, Jinghui Chen, Karsten Vogt, Bodo Rosenhahn
      Improved Threshold Selection by using Calibrated Probabilities for Random Forest Classifiers
      12th Conference on Computer and Robot Vision (CRV), Halifax, Nova Scotia, Canada, June 2015
    • Christoph Reinders, Florian Baumann, Björn Scheuermann, Arne Ehlers, Nicole Mühlpforte, Alfred O. Effenberg, Bodo Rosenhahn
      On-The-Fly Handwriting Recognition using a High-Level Representation
      The 16th International Conference on Computer Analysis of Images and Patterns (CAIP), Lecture Notes in Computer Science (LNCS), Valetta, Malta, September 2015
    • Michele Fenzi, Nico Mentzer, Guillermo Payá-Vayá, Tu Ngoc Nguyen, Thomas Risse, Holger Blume, Jörn Ostermann
      Automatic Situation Assessment for Event-driven Video Analysis
      IEEE International Conference on Advanced Video Signal-Based Surveillance (AVSS), accepted as oral presentation , Seoul, South Korea, August 2014
    • Michael Ying Yang, Bodo Rosenhahn
      Video Segmentation with Joint Object and Trajectory Labeling
      IEEE Winter Conference on Applications of Computer Vision, IEEE, March 2014
    • Michael Ying Yang, Sitong Feng, Bodo Rosenhahn
      Sparse optimization for motion segmentation
      ACCV Workshop on Video Segmentation in Computer Vision, November 2014
    • Florian Baumann, Jie Liao, Arne Ehlers, Bodo Rosenhahn
      Motion Binary Patterns for Action Recognition
      3rd International Conference on Pattern Recognition Applications and Methods, France, Angers Loire Valley, March 2014
    • Florian Baumann, Jie Liao, Arne Ehlers, Bodo Rosenhahn
      Computation Strategies for Volume Local Binary Patterns applied to Action Recognition
      11th IEEE International Conference on Advanced Video and Signal-Based Surveillance , Seoul, Korea, August 2014
    • Florian Baumann, Irina Schulz, Bodo Rosenhahn
      Multi-Sensor Acceleration-based Action Recognition
      International Conference on Image Analysis and Recognition (ICIAR), October 2014
    • Florian Baumann, Li Fangda, Arne Ehlers, Rosenhahn Bodo
      Thresholding a Random Forest Classifier
      Advances in Visual Computing - 10th International Symposium, Springer, Las Vegas, NV, USA, December 2014, edited by George Bebis et al.
    • Oliver Jakob Arndt, Björn Scheuermann, Bodo Rosenhahn
      "Region Cut" - Interactive Multi-Label Segmentation Utilizing Cellular Automaton
      IEEE Workshop on Applications of Computer Vision (WACV), Clearwater Beach, Florida, USA, January 2013
    • Michael Ying Yang
      Image Segmentation by Bilayer Superpixel Grouping
      Asian Conference on Pattern Recognition , accpeted for publication, Okinawa, Japan, November 2013
    • Florian Baumann, Arne Ehlers, Karsten Vogt, Bodo Rosenhahn
      Cascaded Random Forest for Fast Object Detection
      18th Scandinavian Conference on Image Analysis (SCIA), Espoo, Finland, June 2013
    • Florian Baumann
      Action Recognition with HOG-OF Features
      35th German Conference on Pattern Recognition (YRF at GCPR), Saarbrücken, Germany, September 2013
    • Michele Fenzi, Ralf Dragon, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann
      3D Object Recognition and Pose Estimation for Multiple Objects using Multi-Prioritized RANSAC and Model Updating
      Annual Symposium of the German Association for Pattern Recognition (DAGM), accepted as oral presentation , Graz, Austria, August 2012
    • Ralf Dragon, Bodo Rosenhahn, Jörn Ostermann
      Multi-Scale Clustering of Frame-to-Frame Correspondences for Motion Segmentation
      12th European Conference on Computer Vision (ECCV 2012), Florence, October 2012
    • Björn Scheuermann, Markus Schlosser, Bodo Rosenhahn
      Efficient Pixel-Grouping based on Dempster's Theory of Evidence for Image Segmentation
      The 11th Asian Conference on Computer Vision (ACCV), Lecture Notes in Computer Science (LNCS), Springer Berlin/Heidelberg, Vol. 7726, Daejeon, Korea, November 2012, edited by Kyoung Mu Lee, Jim Rehg, Yasuyuki Matsushita, and Zhanyi Hu
    • Michael Ying Yang, Wolfgang Förstner
      A Hierarchical Conditional Random Field Model for Labeling and Classifying Images of Man-made Scenes
      ICCV Workshop on Computer Vision for Remote Sensing of the Environment , IEEE, p. 196 – 203, 2011
    • M. Shoaib, T. Elbrandt, R. Dragon, J. Ostermann
      Altcare: Safe Living For Elderly People
      4th International ICST Conference on Pervasive Computing Technologies for Healthcare 2010, IEEE, March 2010
    • Ralf Dragon, Muhammad Shoaib, Bodo Rosenhahn, Jörn Ostermann
      NF-Features - No-Feature-Features for Representing non-Textured Regions
      11th European Conference on Computer Vision (ECCV 2010), Heraklion, Greece, September 2010
    • M. Shoaib, R. Dragon, J. Ostermann
      Shadow Detection for Moving Humans Using Gradient-Based Background Subtraction
      ICASSP International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan, April 2009
    • M. Shoaib, R. Dragon, J. Ostermann
      Improving Object Detection by Contour-Based Shadow Removal
      Zweiter Workshop optische Technologien – HOT, Hannover, November 2008
  • Journals
    • Jan Voges, Tom Paridaens, Fabian Müntefering, Liudmila S Mainzer, Brian Bliss, Mingyu Yang, Idoia Ochoa, Jan Fostier, Jörn Ostermann, Mikel Hernaez
      GABAC: an arithmetic coding solution for genomic data
      Bioinformatics, Oxford University Press, Vol. 36, No. 7, pp. 2275-2277, December 2019, edited by John Hancock
    • Jan Voges, Jörn Ostermann, Mikel Hernaez
      CALQ: compression of quality values of aligned sequencing data
      Bioinformatics, Oxford University Press, Vol. 34, No. 10, pp. 1650-1658, May 2018, edited by Bonnie Berger
    • Jan Voges, Ali Fotouhi, Jörn Ostermann, M. Oguzhan Külekci
      A Two-level Scheme for Quality Score Compression
      Journal of Computational Biology, Mary Ann Liebert, Inc., Vol. 25, No. 10, October 2018
    • Claudio Alberti, Tom Paridaens, Jan Voges, Daniel Naro, Junaid J. Ahmad, Massimo Ravasi, Daniele Renzi, Giorgio Zoia, Idoia Ochoa, Marco Mattavelli, Jaime Delgado, Mikel Hernaez
      An introduction to MPEG-G, the new ISO standard for genomic information representation
      bioRxiv, Cold Spring Harbor Laboratory, September 2018
    • Michael Ying Yang, Wentong Liao, Hanno Ackermann, Bodo Rosenhahn
      On support relations and semantic scene graphs
      ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, Vol. 131, pp. 15-25, July 2017
    • Ibrahim Numanagic, James K Bonfield, Faraz Hach, Jan Voges, Jörn Ostermann, Claudio Alberti, Marco Mattavelli, S Cenk Sahinalp
      Comparison of high-throughput sequencing data compression tools
      Nature Methods, Nature Publishing Group, Vol. 13, No. 12, pp. 1005-1008, October 2016
    • W. Huang, X. Gong, Michael Ying Yang
      Joint object segmentation and depth upsampling
      Signal Processing Letters, IEEE, Vol. 22, No. 2, p. 192–196, 2015
    • Florian Baumann, Jie Liao, Arne Ehlers, Bodo Rosenhahn
      Recognizing Human Actions using novel Space-time Volume Binary Patterns
      Neurocomputing Journal (to appear), April 2015
    • Ralf Dragon, Carsten Dolar, Jörn Ostermann, Matthias Rieger, Holger Blume, Fabian Abel, Philipp Kärger
      Intelligente Videoüberwachung
      UniMagazin, Vol. 3, pp. 34-37, December 2010
  • Book Chapters
    • Hector Mendoza and Aaron Klein and Matthias Feurer and Jost Tobias Springenberg and Matthias Urban and Michael Burkart and Max Dippel and Marius Lindauer and Frank Hutter
      Towards Automatically-Tuned Deep Neural Networks
      AutoML: Methods, Sytems, Challenges, Springer, pp. 141--156, December 2018, edited by Hutter, Frank and Kotthoff, Lars and Vanschoren, Joaquin
  • Standardisation Contributions
    • Jan Voges, Christian Rohlfing, Viktor Tunev, Yeremia Gunawan, Jörn Ostermann
      Method for the coding of genomic variants
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M52489, Brussels (BE), January 2020
    • Jan Voges, Giorgio Zoia
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M52977, Alpbach (AT) [Online], April 2020
    • Jan Voges, Fabian Müntefering, Yeremia Gunawan Adhisantoso, Junaid Ahmad, Shubham Chandak, Liudmila S Mainzer, Mikel Hernaez, Idoia Ochoa, Jörn Ostermann
      Draft Description of the MPEG-G Reference Encoder Software
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M52978, Alpbach (AT) [Online], April 2020
    • Yeremia Gunawan Adhisantoso, Viktor Tunev, Jan Voges, Christian Rohlfing
      MPEG-G Part 6 CE3 Results Leibniz University Hannover, RWTH Aachen University
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M53496, Alpbach (AT) [Online], April 2020
    • Jan Voges, Mikel Hernaez, Idoia Ochoa
      Results of Core Experiment 3
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M53713, Alpbach (AT) [Online], April 2020
    • Jan Voges
      MPEG-G Part 6 CE3 Cross-Check of UIUC/University of Navarra Results
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M53789, Alpbach (AT) [Online], April 2020
    • Jan Voges, Idoia Ochoa, Mikel Hernaez, Fabian Müntefering, Giorgio Zoia
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M45266, Marrakesh (MA), January 2019
    • Paolo Ribeca, Jan Voges, Tom Paridaens, Mikel Hernaez, Idoia Ochoa, Claudio Alberti, Marco Mattavelli, Giuseppe Codispoti, Jaime Delgado, Daniel Naro
      Thoughts on future standardization activities in the area of genomic information representation
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M45267, Marrakesh (MA), January 2019
    • Jan Voges, Tom Paridaens, Daniel Naro, Dmitry Repchevski, Jaime Delgado, Mikel Hernaez
      Study on ISO/IEC 23092-2
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M45294, Marrakesh (MA), January 2019
    • Daniel Naro, Jan Voges, Tom Paridaens, Dmitry Repchevski, Jaime Delgado, Paolo Ribeca, Idoia Ochoa, Mikel Hernaez
      Comments on ISO/IEC DIS 23092-1 and ISO/IEC DIS 23092-2
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M45601, Marrakesh (MA), January 2019
    • Massimo Ravasi, Daniel Naro, Junaid Ahmad, Jan Voges
      Current status of MPEG-G reference software implementation
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M46068, Marrakesh (MA), January 2019
    • Jan Voges, Idoia Ochoa, Mikel Hernaez, James Bonfield
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M46660, Geneva (CH), March 2019
    • Massimo Ravasi, Daniel Naro, Junaid Ahmad, Jan Voges, Tom Paridaens
      Current status of MPEG-G reference software implementation
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M47166, Geneva (CH), March 2019
    • Jan Voges, Idoia Ochoa, Mikel Hernaez, Giorgio Zoia, Marco Mattavelli
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M48100, Gothenburg (SE), July 2019
    • Dunling Li, Claudio Alberti, Jaime Delgado, Jan Voges, Itaru Kaneko, Marco Mattavelli, Patrick Cheung, Paolo Ribeca
      MPEG-G Best Practices Deployment Guide
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M50913, Geneva (CH), October 2019
    • Christian Rohlfing, Viktor Tunev, Jan Voges
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M51192, Geneva (CH), October 2019
    • Jan Voges
      Study on White paper on the objectives and benefits of the MPEG-G standard (Draft 1)
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M41956, Gwangju (KR), January 2018
    • Massimo Ravasi, Daniel Naro, Junaid Ahmad, Jan Voges
      Current status of MPEG-G reference software implementation
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M42083, Gwangju (KR), January 2018
    • Jan Voges
      Study of ISO/IEC 23092-2
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M42305, San Diego, CA (US), April 2018
    • Jan Voges
      Quality value coding and functional equivalence of genomic analysis pipelines
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M42306, San Diego, CA (US), April 2018
    • Jan Voges
      Study of ISO/IEC CD 23092-3
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M42919, Ljubljana (SI), July 2018
    • Jan Voges, Idoia Ochoa, Mikel Hernaez
      Update to the genomic information database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M42920, Ljubljana (SI), July 2018
    • Jan Voges, Idoia Ochoa, Mikel Hernaez
      Proposed Updates to the MPEG-G Genomic Information Database
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M44035, Macao (MO), October 2018
    • Jan Voges, Shubham Chandak, Mikel Hernaez
      Study on ISO/IEC DIS 23092-2
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M44049, Macao (MO), October 2018
    • Jan Voges
      Core Experiment 2 summary
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39663, Geneva (CH), January 2017
    • Jan Voges, Mikel Hernaez
      Core Experiment 2 results LUH-Stanford/UIUC
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39664, Geneva (CH), January 2017
    • Jan Voges
      Core Experiment 1 results LUH
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39665, Geneva (CH), January 2017
    • Jan Voges
      Core Experiment 3 results LUH
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39666, Geneva (CH), January 2017
    • Jan Voges, Mikel Hernaez
      Core Experiment 2 on Genomic Information Representation results LUH/Stanford/UIUC
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40224, Hobart (AU), April 2017
    • Jan Voges, Claudio Alberti, Mikel Hernaez, Tom Paridaens, James Bonfield, Paolo Ribeca, Jaime Delgado
      Unified representation of sequencing quality values
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40222, Hobart (AU), April 2017
    • Jan Voges
      Summary of Core Experiment 2 on Genomic Information Representation
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40223, Hobart (AU), April 2017
    • Claudio Alberti, Jan Voges, Giorgio Zioa
      Unified representation of genomic reads
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40277, Hobart (AU), April 2017
    • Jan Voges
      Core Experiment 5 on Genomic Information Representation results LUH
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40804, Turin (IT), July 2017
    • Jan Voges
      Proposed changes for ISO/IEC 23092-2 WD 2
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40860, Turin (IT), July 2017
    • Jan Voges
      A Rate-Distortion Analysis of Sequencing Quality Value Compression
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M40861, Turin (IT), July 2017
    • Claudio Alberti, Jan Voges
      Study on ISO/IEC 23092-2 WD 3
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M41393, Macao (CN), October 2017
    • Jan Voges
      Core Experiment 1 cross-check SFU
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39748, Geneva (CH), January 2017
    • Jan Voges
      Core Experiment 2 cross-check SFU
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39749, Geneva (CH), January 2017
    • Jan Voges
      Core Experiment 3 cross-check SFU
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M39750, Geneva (CH), January 2017
    • Jan Voges
      Reference-free Compression of Aligned Next-Generation Sequencing Data
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37678, San Diego, CA (US), February 2016
    • Ibrahim Numanagic, Faraz Hach, James Bonfield, Claudio Alberti, Jan Voges
      Review of genomic information compression tools
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37766, San Diego, CA (US), February 2016
    • Claudio Alberti, Marco Mattavelli, Ana A. Hernandez-Lopez, Mikel Hernaez, Rachel G. Goldfeder, Noah Daniels, Jan Voges
      Proposal for the update to the database of genomic test data
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37767, San Diego, CA (US), February 2016
    • Claudio Alberti, Marco Mattavelli, Ana A. Hernandez-Lopez, Noah Daniels, Mikel Hernaez, Idoia Ochoa, Jan Voges, Rachel Goldfeder, Daniel Greenfield
      Evaluation framework for lossy compression of genomic Quality Values
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37768, San Diego, CA (US), February 2016
    • Jan Voges, Mikel Hernaez, Ana Angelica Hernandez-Lopez, Claudio Alberti, Marco Mattavelli, Al Wegener, Dan Greenfield, Noah Daniels, S Cenk Sahinalp, James Bonfield, Bonnie Berger
      Extensions and notes to the evaluation framework for lossy compression of genome sequencing quality values
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M38376, Geneva (CH), May 2016
    • Jan Voges, Mikel Hernaez, Idoia Ochoa, Ana Angelica Hernandez-Lopez, Claudio Alberti, Marco Mattavelli, Al Wegener, Dan Greenfield, Noah Daniels, S Cenk Sahinalp, James Bonfield, Bonnie Berger, Jörn Ostermann
      Benchmark framework for lossy compression of genome sequencing quality values
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M38916, Chengdu (CN), October 2016
    • Jan Voges, Mikel Hernaez, Jörn Ostermann
      Adaptive lossy compression of high-throughput sequencing quality values
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M38917, Chengdu (CN), October 2016
    • Jan Voges, Marco Munderloh, Jörn Ostermann
      Reference-free compression of aligned high-throughput sequencing data
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M38918, Chengdu (CN), October 2016
    • Jan Voges, Marco Munderloh
      Approaches to SAM File Compression
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M36282, Warsaw (PL), June 2015
    • Jan Voges
      A Framework for the Evaluation of Genomic Information Compression
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37061, Geneva (CH), October 2015
    • Claudio Alberti, Marco Mattavelli, Ioannis Xenarios, Nicolas Guex, Heinz Stockinger, Thierry Schuepbach, Christian Iseli, Daniel Zerzion, Ivan Topolsky, Yann Thoma, Enrico Petraglio, Mikel Hernaez, Jan Voges
      A framework for the comparison of genomic information compression tools
      ISO/IEC JTC 1/SC 29/WG 11, Document Number M37151, Geneva (CH), October 2015
  • Technical Report
    • Artur Souza, Luigi Nardi, Leonardo Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter
      Prior-guided Bayesian Optimization
      arxiv:2006.14608[cs.LG], June 2020
    • Lucas Zimmer, Marius Lindauer, Frank Hutter
      Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
      arxiv:2006.13799[cs.LG], June 2020
    • Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
      Auto-Sklearn 2.0: The Next Generation
      arXiv:2007.04074 [cs.LG], July 2020
    • M. Lindauer and K. Eggensperger and M. Feurer and A. Biedenkapp and J. Marben and P. M\"uller and F. Hutter
      BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters
      arXiv:1908.06756 [cs.LG], August 2019
    • Marius Lindauer and Frank Hutter
      Best Practices for Scientific Research on Neural Architecture Search
      Arxiv/CoRR, September 2019