Jun.-Prof. Dr. rer. nat. Tanya Braun
- Alumni, former Research Assistant -
ACHTUNG: Am 1. November 2021 bin ich zur WWU Münster gewechselt (Mitteilung der WWU Münster).
Mein neuer Internetauftritt findet sich hier: https://www.uni-muenster.de/Informatik.AGBraun/
Die Seite hier wird nicht mehr aktualisiert!
Publikationen am IFIS
Alle:DBLP
Alle:Google Scholar
Alle:Semantic Scholar
CV
- Seit November 2021 Juniorprofessorin und Leiterin der Arbeitsgruppe Data Science an der WWU Münster
- Februar 2020 - Promotion (Dissertationsschrift, Kolloquiumsfolien)
- Dezember 2015 - 31. Oktober 2021 wissenschaftliche Mitarbeiterin am Institut für Informationssysteme der Universität zu Lübeck
- September 2015 - M.Sc. in Computational Informatics, Technische Universität Hamburg-Harburg
- August 2009 - B.A. hons in Business Administration, University of Sunderland
Forschungsinteressen
Meine Forschungsinteressen liegen hauptsächlich in den genannten Themenbereichen:
- Statistisch-relationale KI (Statistical relational AI, StarAI), besonders probabilistische Inferenz in relationalen Domänen
- Textverständnis, besonders Annotationen und Kontextdarstellungen
- mensch-bewusste KI, besonders Online Entscheidungen durch mensch-bewusste Agenten
Meine Doktorarbeit gehört zum Bereich StarAI und hat den Lifted Junction Tree Algorithmus (LJT) als zentrales Thema. Nähere Informationen zu LJT finden Sie hier.
Lehre
Meine aktuelle Lehrtätigkeit finden Sie hier.
Vorlesung
- Intelligente Agenten (MA, englisch, 4VL, 2Üb, WiSe2020/21, zusammen mit Ralf Möller); Teil der Vorlesung + Übung
- Advanced Topics Data Science and AI: Automated Planning and Acting (MA, englisch, 2VL, 1Üb, SoSe2020); Vorlesung + Übung
- MOBI-DBS-B: Datenbanksysteme, Lehrauftrag Otto-Friedrich-Universität Bamberg (BA, Sommer 2019)
Übungsleitung
- Algorithmen und Datenstrukturen (BA 2. Sem., Sommer, 4VL, 2Üb, 2016-2019)
- Einführung in Web und Data Science (BA 1. Sem., Winter, 2VL, 1Üb, 2016/17-2019/20)
- Non-standard Datenbanken und Data Mining (BA 5. Sem., Winter, 4VL, 2Üb, 2018/19-2019/20)
- Web Mining Agents (MA, englisch, Winter, 4VL, 2Üb, 2015/16-2017/18)
Wissenschaftliche Aktivitäten
Herausgeberschaft
- Handbuch der Künstlichen Intelligenz, 6. Auflage, in Zusammenarbeit mit Günther Görz und Ute Schmid, Verlag: De Gruyter, Link zur Verlagsseite
- Special Issue on Conceptual Structures 2020, Annals of Mathematics and Artificial Intelligence, in Zusammenarbeit mit Mehwish Alam, Dominik Endres und Bruno Yun, Verlag: Springer, Call for papers
Organisation
- 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), Rhodes, Greece, Doctoral Consortium Chair (call)
- 27th International Conference on Conceptual Strucutres, September, Münster, Germany (ICCS 2022), General Chair
- 44th German Conference on Artificial Intelligence, September 27-October 1, 2021, Berlin, Germany (KI2021), Workshop & Tutorials Chair
- 26th International Conference on Conceptual Strucutres, September, Bolzano, Italy (ICCS 2021), General Chair
- 43rd German Conference on Artificial Intelligence, September 21–25, 2020, Bamberg, Germany (KI2020), Doctoral Consortium Chair (call)
- 25th International Conference on Conceptual Strucutres, September 18-21, Bolzano, Italy (ICCS 2020), Co-Program Chair (call)
Eingeladene Vorträge
- Vortrag im Geoinformatik Forum mit dem Titel "A Glimpse into Statistical Relational AI - Indistinguishability for the Win!", Folien hier
- Vortrag beim WWU Resilienzkolloquium mit dem Titel "Inference Techniques for Resilience", 9.11.2022, Folien hier
- Vortrag bei der Woche der KI Lübeck mit dem Titel "The More, the Merrier: The Power of Relations for Probabilistic Graphical Models", 3.11.2022, Folien hier
- Vortrag beim Workshop "Robust AI for High-stakes Applications@KI-22" mit dem Titel "Statistical Relational AI and Robustness", 20.09.2022, virtuell, Folien hier
- Vortrag beim Workshop "Data Linking for Humanities Research" mit dem Titel "To Extend or Not to Extend? Context-driven Corpus Enrichment", 21.10.2019, Hamburg, Folien hier
- Präsentation des Forschungsprojekts LJT am Institut für Medizinische Elektrotechnik, 16.1.2018, Lübeck, Folien hier
Tutorials
- Eingeladen: A Glimpse into Statistical Relational AI: The Power of Indistinguishability, auf der SUM 2022, 18.10.2022, Webseite hier
- StaRAI - Semantics and Symmetries in Exact Lifted Inference, auf der ECAI 2020, in Zusammenarbeit mit Marcel Gehrke, 29-30.08.2020
- StaRAI - Semantics and Inference auf der FLAIRS-33, in Zusammenarbeit mit Marcel Gehrke, Prof. Dr. Gabriele Kern-Isberner und Marco Wilhelm, 17.-20.05.2020 (FLAIRS-33 wurde abgesagt)
- Dynamic StarAI auf der KI 2019 in Zusammenarbeit mit Marcel Gehrke und Ralf Möller, 23.-26.09.2019
- Inference in Statistical Relational AI auf der ICCS 2019 in Zusammenarbeit mit Marcel Gehrke, 01.-04.07.2019
- StarAI or StarDB? auf der BTW 2019, 04.03.2019
- StarAI auf der KI-18 in Zusammenarbeit mit Kristian Kersting und Ralf Möller, 24.09.18 (Folien hier verfügbar)
Folien für Konferenz/Workshop-Papiere (für Papiere, bei denen ich den Vortrag gehalten habe; der Name des Links bezieht sich auf den Titel des Papiers)
- To Extend or not to Extend? Complementary Documents
- Restricting the Maximum Number of Actions for Decision Support under Uncertainty
- Lifting Queries for Lifted Inference (Highlight-Artikel auf der ECAI-2020 von einem IJCAI-2018-Artikel)
- Exploring Unknown Universes in Probabilistic Relational Models
- To Extend or not to Extend? Context-specific Corpus Enrichment
- Uncertain Evidence for Probabilistic Relational Models
- Adaptive Inference on Probabilistic Relational Models
- Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm
- Parameterised Queries and Lifted Query Answering
- Lifted Most Probable Explanation
- Preventing Groundings and Handling Evidence in the Lifted Junction Tree Algorithm
- Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm
- Lifted Junction Tree Algorithm
Reviews
Studentische Projekte
- Moritz Hoffmann: Aufbereitung des Projektscodes für LJT und LDJT; siehe LJT Implementierung und LDJT Implementierung.
- Florian Marwitz: Kompaktifizierung von lokalen Verteilungen zur Generierung von Regeln.
- Tristan Potten: Framework zum Benchmarken von Algorithmen zur Anfragebeantwortung in probabilistischen Modellen von der Generieren der Modelle bis zur Sammlung von Statistikwerten; siehe GitHub-Projekt und Veröffentlichung.
Publikationen
2018
Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm, in Proceedings of the AI 2018: Advances in Artificial Intelligence , Springer, Dec.2018. pp. 556--562.
DOI: | https://doi.org/10.1007/978-3-030-03991-2_51 |
ISBN: | 978-3-030-03991-2 |
File: | 1807.00744 |
Bibtex: | ![]() @inproceedings{GehBrMo18e, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm}}, booktitle = {Proceedings of the AI 2018: Advances in Artificial Intelligence}, year = {2018}, pages={556--562}, publisher = {Springer}, isbn={978-3-030-03991-2}, doi={https://doi.org/10.1007/978-3-030-03991-2_51} } |
Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm, in Proceedings of KI 2018: Advances in Artificial Intelligence , Springer, Sep.2018. pp. 38--45.
DOI: | https://doi.org/10.1007/978-3-030-00111-7_4 |
ISBN: | 978-3-030-00111-7 |
Bibtex: | ![]() @inproceedings{GehBrMo18c, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm}}, booktitle = {Proceedings of {KI} 2018: Advances in Artificial Intelligence}, year = {2018}, pages={38--45}, publisher = {Springer}, doi = {https://doi.org/10.1007/978-3-030-00111-7_4}, isbn={978-3-030-00111-7} } |
Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm, in Proceedings of KI 2018: Advances in Artificial Intelligence , Springer, Sep.2018. pp. 24--37.
DOI: | https://doi.org/10.1007/978-3-030-00111-7_3 |
ISBN: | 978-3-030-00110-0 |
File: | 1807.00743 |
Bibtex: | ![]() @inproceedings{BraMo18d, author = {Tanya Braun and Ralf M\"oller}, title = {{Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm}}, booktitle = {Proceedings of {KI} 2018: Advances in Artificial Intelligence}, year = {2018}, pages = {24--37}, publisher = {Springer}, isbn = {978-3-030-00110-0}, doi = {https://doi.org/10.1007/978-3-030-00111-7_3} } |
Answering Hindsight Queries with Lifted Dynamic Junction Trees, in 8th International Workshop on Statistical Relational AI at the 27th International Joint Conference on Artificial Intelligence , 072018.
File: | 1807.01586 |
Bibtex: | ![]() @inproceedings{GehBrMo18b, author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller}, title = {{Answering Hindsight Queries with Lifted Dynamic Junction Trees}}, booktitle = {8th International Workshop on Statistical Relational AI at the 27th International Joint Conference on Artificial Intelligence}, year = {2018}, url = {https://arxiv.org/abs/1807.01586} } |
Lifted Most Likely Explanation, in Proceedings of the International Conference on Conceptual Structures , Springer, 072018.
Parameterised Queries and Lifted Query Answering, in IJCAI-18 Proceedings of the 27th International Joint Conference on Artificial Intelligence , International Joint Conferences on Artificial Intelligence Organization, Jul.2018. pp. 4980--4986.
DOI: | https://doi.org/10.24963/ijcai.2018/691 |
Bibtex: | ![]() @inproceedings{BraMo18b, author = {Tanya Braun and Ralf M\"oller}, title = {{Parameterised Queries and Lifted Query Answering}}, booktitle = {IJCAI-18 Proceedings of the 27th International Joint Conference on Artificial Intelligence}, publisher = {International Joint Conferences on Artificial Intelligence Organization}, pages = {4980--4986}, year = {2018}, doi = {https://doi.org/10.24963/ijcai.2018/691} } |
Towards Lifted Maximum Expected Utility, in Proceedings of the First Joint Workshop on Artificial Intelligence in Health in Conjunction with the 27th IJCAI, the 23rd ECAI, the 17th AAMAS, and the 35th ICML , CEUR-WS.org, 072018. pp. 93--96.
File: | |
Bibtex: | ![]() @inproceedings{Gehrke2018TLMEU, Author = {Marcel Gehrke and Tanya Braun and Ralf M\"oller and Alexander Waschkau and Christoph Strumann and Jost Steinhäuser}, Title = {{Towards Lifted Maximum Expected Utility}}, Year = {2018}, Booktitle={Proceedings of the First Joint Workshop on Artificial Intelligence in Health in Conjunction with the 27th IJCAI, the 23rd ECAI, the 17th AAMAS, and the 35th ICML}, series = {{CEUR} Workshop Proceedings}, volume = {2142}, year = {2018}, pages = {93--96}, publisher = {CEUR-WS.org}, url = {http://ceur-ws.org/Vol-2142/short8.pdf}} |
Lifted Dynamic Junction Tree Algorithm, in Proceedings of the International Conference on Conceptual Structures , Springer, 062018. pp. 55--69.
DOI: | https://doi.org/10.1007/978-3-319-91379-7_5 |
File: | Dateilink |
Bibtex: | ![]() @inproceedings{gehrke2018ldjt, author={Marcel Gehrke and Tanya Braun and Ralf M{\"o}ller}, title={{Lifted Dynamic Junction Tree Algorithm}}, booktitle={Proceedings of the International Conference on Conceptual Structures}, year={2018}, pages = {55--69} publisher={Springer}, doi = {https://doi.org/10.1007/978-3-319-91379-7_5} } |
Lifted Most Probable Explanation, in Proceedings of the International Conference on Conceptual Structures , Springer, 062018. pp. 39--54.
DOI: | https://doi.org/10.1007/978-3-319-91379-7_4 |
Bibtex: | ![]() @inproceedings{BraMo18a, author={Tanya Braun and Ralf M{\"o}ller}, title={{Lifted Most Probable Explanation}}, booktitle={Proceedings of the International Conference on Conceptual Structures}, year={2018}, pages = {39--54}, publisher={Springer}, doi = {https://doi.org/10.1007/978-3-319-91379-7_4} } |
Adaptive Inference on Probabilistic Relational Models, in AI 2018: Advances in Artificial Intelligence , Springer, 2018. pp. 487--500.
DOI: | https://doi.org/10.1007/978-3-030-03991-2_44 |
Bibtex: | ![]() @inproceedings{BraMo18e, author = {Tanya Braun and Ralf M\"oller}, title = {{Adaptive Inference on Probabilistic Relational Models}}, booktitle = {AI 2018: Advances in Artificial Intelligence}, pages = {487--500}, year = {2018}, publisher = {Springer}, doi = {https://doi.org/10.1007/978-3-030-03991-2_44} } |
Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm - Extended Version, in Postproceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning , Springer, 2018. pp. 54--72.
DOI: | https://doi.org/10.1007/978-3-319-78102-0_3 |
Bibtex: | ![]() @inproceedings{BraMo18, author = {Tanya Braun and Ralf M\"oller}, title = {{Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm - Extended Version}}, booktitle = {Postproceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning}, publisher = {Springer}, year = {2018}, pages = {54--72}, doi = {https://doi.org/10.1007/978-3-319-78102-0_3} } |
2017
Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm, in Graph Structures for Knowledge Representation and Reasoning - 5th International Workshop (GKR 2017), Melbourne, Australia , 2017.
File: | papers.html |
Bibtex: | ![]() @inproceedings{BraMo17, author = {Tanya Braun and Ralf M\"oller}, title = {{Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm}}, booktitle = {Graph Structures for Knowledge Representation and Reasoning - 5th International Workshop (GKR 2017), Melbourne, Australia}, year = {2017}, url = {http://www.lirmm.fr/~hecham/GKR/papers.html} } |
Preventing Groundings and Handling Evidence in the Lifted Junction Tree Algorithm, in KI 2017: Advances in Artificial Intelligence , Springer, 2017. pp. 85--98.
DOI: | https://doi.org/10.1007/978-3-319-67190-1_7 |
Bibtex: | ![]() @inproceedings{BraMo17a, author = {Tanya Braun and Ralf M\"oller}, title = {{Preventing Groundings and Handling Evidence in the Lifted Junction Tree Algorithm}}, booktitle = {KI 2017: Advances in Artificial Intelligence}, pages = {85--98}, year = {2017}, publisher = {Springer}, doi = {https://doi.org/10.1007/978-3-319-67190-1_7} } |
2016
"Lifted Junction Tree Algorithm" 2016.
Lifted Junction Tree Algorithm, in KI 2016: Advances in Artificial Intelligence , Springer, 2016. pp. 30--42.
DOI: | http://dx.doi.org/10.1007/978-3-319-46073-4 |
Bibtex: | ![]() @inproceedings{BrMoe16a, author = {Tanya Braun and Ralf M\"oller}, title = {Lifted Junction Tree Algorithm}, booktitle = {{KI} 2016: Advances in Artificial Intelligence}, publisher = {Springer}, year = {2016}, pages = {30--42}, doi = {http://dx.doi.org/10.1007/978-3-319-46073-4} } |

- Team
- Umut Çalıkyılmaz
- Rebecca von Engelhardt
- Björn Filter
- Nils Fußgänger
- Jinghua Groppe
- Sven Groppe
- Tobias Groth
- Mattis Hartwig
- Nils Wendel Heinrich
- Akasha Kessel
- Hanieh Khorashadizadeh
- Malte Luttermann
- Jörg-Uwe Meyer
- Jeannette Mödlhammer
- Nitin Nayak
- Simon Paasche
- Michael Preisig
- Nele Rußwinkel
- Simon Schiff
- Tim Schulz
- Thomas Sievers
- Tobias Winker
- Alumni