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Eine Ebene höherGruppiert nach: Dokumententyp |
Veröffentlichungsdatum
Anzahl der Publikationen: 41
2023
Ding, Zifeng; Wu, Jingpei; Li, Zongyue; Ma, Yunpu 
ORCID: https://orcid.org/0000-0001-6112-8794 und Tresp, Volker ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Turin, Italy, Sep 18-22, 2023.
Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis, Elena und Bonchi, Francesco (Hrsg.):
In: Machine Learning and Knowledge Discovery in Databases: Research Track,
Bd. 14171
Cham: Springer. S. 550-566
ORCID: https://orcid.org/0000-0001-6112-8794 und Tresp, Volker ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Turin, Italy, Sep 18-22, 2023.
Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis, Elena und Bonchi, Francesco (Hrsg.):
In: Machine Learning and Knowledge Discovery in Databases: Research Track,
Bd. 14171
Cham: Springer. S. 550-566
Zhang, Yao; Ma, Yunpu ORCID: https://orcid.org/0000-0001-6112-8794; Seidl, Thomas und Tresp, Volker ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Adaptive Multi-Resolution Attention with Linear Complexity.
2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 18-23 June 2023.
In: IJCNN 2023, International Joint Conference on Neural Networks, 18-23 June 2023, Gold Coast Convention and Exhibition Centre, Queensland, Australia,
Piscataway, NJ, USA: IEEE.
ORCID: https://orcid.org/0000-0001-6112-8794; Seidl, Thomas und Tresp, Volker ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Adaptive Multi-Resolution Attention with Linear Complexity.
2023 International Joint Conference on Neural Networks (IJCNN), Gold Coast, Australia, 18-23 June 2023.
In: IJCNN 2023, International Joint Conference on Neural Networks, 18-23 June 2023, Gold Coast Convention and Exhibition Centre, Queensland, Australia,
Piscataway, NJ, USA: IEEE.
Decker, Thomas; Lebacher, Michael und Tresp, Volker ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts.
2023 IEEE 21st International Conference on Industrial Informatics (INDIN), Lemgo, Germany, 18-20 July 2023.
Jasperneite, Jürgen (Hrsg.):
In: 2023 IEEE 21st International Conference on Industrial Informatics : INDIN 2023 : 17-20 July 2023, Lemgo, Germany,
[Piscataway, NJ]: IEEE.
ORCID: https://orcid.org/0000-0001-9428-3686
(2023):
Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts.
2023 IEEE 21st International Conference on Industrial Informatics (INDIN), Lemgo, Germany, 18-20 July 2023.
Jasperneite, Jürgen (Hrsg.):
In: 2023 IEEE 21st International Conference on Industrial Informatics : INDIN 2023 : 17-20 July 2023, Lemgo, Germany,
[Piscataway, NJ]: IEEE.
Giovagnoli, Alessandro; Tresp, Volker; Ma, Yunpu und Schubert, Matthias
(2023):
QNEAT: Natural Evolution of Variational Quantum Circuit Architecture.
GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation, Lisbon Portugal, July 15 - 19, 2023.
Silva, Sara und Paquete, Luís (Hrsg.):
In: GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation,
New York: Association for Computing Machinery. S. 647-650
2022
Gu, Jindong; Zhao, Hengshuang; Tresp, Volker und Qin, Yao
(2022):
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness.
Computer Vision – ECCV 2022, Tel Aviv, Israel, October 23–27, 2022.
Avidan, Shai; Brostow, Gabriel; Cissé, Moustapha; Farinella, Giovanni Maria und Hassner, Tal (Hrsg.):
In: Computer Vision – ECCV 2022. 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXIX,
Bd. 13689
Springer. S. 308-325
Gu, Jindong; Tresp, Volker und Qin, Yao
(2022):
Are Vision Transformers Robust to Patch Perturbations?
Computer Vision – ECCV 2022, Tel Aviv, Israel, October 23–27, 2022.
Avidan, Shai; Brostow, Gabriel; Cissé, Moustapha; Farinella, Giovanni Maria und Hassner, Tal (Hrsg.):
In: Computer Vision – ECCV 2022. 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part I,
Bd. 13672
Springer. S. 404-421
Frikha, Ahmed; Krompaß, Denis und Tresp, Volker
(2022):
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption.
26th International Conference on Pattern Recognition (ICPR), Montreal, QC, Canada, 21-25 August 2022.
In: 26th International Conference on Pattern Recognition (ICPR),
S. 1871-1878
Shit, Suprosanna ORCID: https://orcid.org/0000-0003-4435-7207; Koner, Rajat ORCID: https://orcid.org/0000-0003-3441-8192; Wittmann, Bastian; Paetzold, Johannes; Ezhov, Ivan; Li, Hongwei; Pan, Jiazhen; Sharifzadeh, Sahand; Kaissis, Georgios; Tresp, Volker und Menze, Bjoern
(2022):
Relationformer: A Unified Framework for Image-to-Graph Generation.
17th European Conference on Computer Vision (ECCV 2022), Tel Aviv, Israel, October 23–27, 2022.
Avidan, Shai; Brostow, Gabriel; Cissé, Moustapha; Farinella, Giovanni Maria und Hassner, Tal (Hrsg.):
In: Computer Vision – ECCV 2022, Lecture Notes in Computer Science
Bd. 13697
Cham, Switzerland: Springer. S. 422-439
ORCID: https://orcid.org/0000-0003-4435-7207; Koner, Rajat ORCID: https://orcid.org/0000-0003-3441-8192; Wittmann, Bastian; Paetzold, Johannes; Ezhov, Ivan; Li, Hongwei; Pan, Jiazhen; Sharifzadeh, Sahand; Kaissis, Georgios; Tresp, Volker und Menze, Bjoern
(2022):
Relationformer: A Unified Framework for Image-to-Graph Generation.
17th European Conference on Computer Vision (ECCV 2022), Tel Aviv, Israel, October 23–27, 2022.
Avidan, Shai; Brostow, Gabriel; Cissé, Moustapha; Farinella, Giovanni Maria und Hassner, Tal (Hrsg.):
In: Computer Vision – ECCV 2022, Lecture Notes in Computer Science
Bd. 13697
Cham, Switzerland: Springer. S. 422-439
Li, Hang; Khan, Qadeer; Tresp, Volker und Cremers, Daniel
(2022):
Biologically Inspired Neural Path Finding.
15th International Conference on Brain Informatics (BI 2022), Padua, Italy, July 15–17, 2022.
Mahmud, Mufti; He, Jing; Vassanelli, Stefano; Zundert, André van und Zhong, Ning (Hrsg.):
In: Brain Informatics, Lecture Notes in Computer Science
Bd. 13406
Cham: Springer. S. 329-342
Liu, Tong; Liu, Yushan; Hildebrandt, Marcel; Joblin, Mitchell; Li, Hang und Tresp, Volker
(2022):
On Calibration of Graph Neural Networks for Node Classification.
2022 International Joint Conference on Neural Networks (IJCNN), Padua. Italy, 30 September 2022.
In: 2022 International Joint Conference on Neural Networks (IJCNN),
Piscataway, NJ, USA: IEEE. S. 1-8
Ali, Mehdi; Berrendorf, Max; Hoyt, Charles Tapley; Vermue, Laurent; Galkin, Mikhail; Sharifzadeh, Sahand; Fischer, Asja; Tresp, Volker und Lehmann, Jens
(2022):
Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Bd. 44, Nr. 12: S. 8825-8845
2021
Gu, Jindong; Zhao, Rui und Tresp, Volker
(2021):
Semantics for Global and Local Interpretation of Deep Convolutional Neural Networks.
2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, 18-22 July 2021.
In: 2021 International Joint Conference on Neural Networks (IJCNN),
IEEE. S. 1-8
Ma, Yunpu und Tresp, Volker
(2021):
Causal Inference under Networked Interference and Intervention Policy Enhancement.
In: 24Th International Conference on Artificial Intelligence and Statistics (Aistats), Bd. 130
Ali, Mehdi; Berrendorf, Max; Hoyt, Charles Tapley; Vermue, Laurent; Sharifzadeh, Sahand; Tresp, Volker und Lehmann, Jens
(2021):
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.
In: Journal of Machine Learning Research, Bd. 22, 2021
Sharifzadeh, Sahand; Moayed Baharlou, Sina und Tresp, Volker
(2021):
Classification by Attention: Scene Graph Classification with Prior Knowledge.
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Virtual Event, February 2-9, 2021.
In: Proceedings of the AAAI Conference on Artificial Intelligence,
Bd. 35, Nr. 6
AAAI Press. S. 5025-5033
Frikha, Ahmed; Krompaß, Denis; Köpken, Hans-Georg und Tresp, Volker
(2021):
Few-Shot One-Class Classification via Meta-Learning.
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Virtual Event, February 2-9, 2021.
Proceedings of the AAAI Conference on Artificial Intelligence.
Bd. 35, Nr. 8
AAAI Press. S. 7448-7456
Koner, Rajat; Li, Hang; Hildebrandt, Marcel; Das, Deepan; Tresp, Volker und Günnemann, Stephan
(2021):
Graphhopper: Multi-hop Scene Graph Reasoning for Visual Question Answering.
In: Hotho, Abdreas; Blomquist, Eva; Dietze, Stefan; Fokoue, Achille; Ding, Ying; Barnaghi, Payam; Haller, Armin; Dragoni, Mauro und Alani, Harith (Hrsg.):
The Semantic Web – ISWC 2021 : 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24–28, 2021, Proceedings. Lecture Notes in Computer Science (LNCS), Bd. 12922. Cham: Springer. S. 111-127
Liu, Yushan; Hildebrandt, Marcel; Joblin, Mitchell; Ringsquandl, Martin; Raissouni, Rime und Tresp, Volker
(2021):
Neural Multi-hop Reasoning with Logical Rules on Biomedical Knowledge Graphs.
In: Verborgh, Ruben; Hose, Katja; Paulheim, Heiko; Champin, Pierre-Antoine; Maleshkova, Maria; Corcho, Oskar; Ristoski, Petar und Alam, Mehwish (Hrsg.):
The Semantic Web. 18th International Conference, ESWC 2021, Virtual Event, June 6–10, 2021, Proceedings. Lecture Notes in Computer Science (LNCS), Bd. 12731. Cham: Springer. S. 375-391
Sharifzadeh, Sahand; Baharlou, Sina Moayed; Berrendorf, Max; Koner, Rajat und Tresp, Volker
(2021):
Improving Visual Relation Detection using Depth Maps.
2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, 10-15 January 2021.
In: 2020 25th International Conference on Pattern Recognition (ICPR),
New York: IEEE. S. 3597-3604
Frikha, Ahmed; Krompass, Denis und Tresp, Volker
(2021):
ARCADe: A Rapid Continual Anomaly Detector.
2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, 10-15 January 2021.
In: 2020 25th International Conference on Pattern Recognition (ICPR),
New York: IEEE. S. 10449-10456
Gu, Jindong; Tresp, Volker und Hu, Han
(2021):
Capsule Network is Not More Robust than Convolutional Network.
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, 20-25 June 2021.
In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
New York: IEEE. S. 14304-14312
2020
Gu, Jindong und Tresp, Volker
(2020):
Search for Better Students to Learn Distilled Knowledge.
In: ECAI 2020: 24th European Conference on Artificial Intelligence, Bd. 325: S. 1159-1165
Gu, Jindong und Tresp, Volker
(2020):
Improving the Robustness of Capsule Networks to Image Affine Transformations.
In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): S. 7283-7291
Ravanbakhsh, Mahdyar; Tschernezki, Vadim; Last, Felix; Klein, Tassilo; Batmanghelich, Kayhan; Tresp, Volker und Nabi, Moin
(2020):
HUMAN-MACHINE COLLABORATION FOR MEDICAL IMAGE SEGMENTATION.
In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing: S. 1040-1044
Hildebrandt, Marcel; Serna, Jorge Andres Quintero; Ma, Yunpu; Ringsquandl, Martin; Joblin, Mitchell und Tresp, Volker
(2020):
Reasoning on Knowledge Graphs with Debate Dynamics.
In: Thirty-Fourth Aaai Conference on Artificial Intelligence, the Thirty-Second Innovative Applications of Artificial Intelligence Conference and the Tenth Aaai Symposium on Educational Advances in Artificial Intelligence, Bd. 34: S. 4123-4131
Carrami, Eli M.; Sharifzadeh, Sahand; Wietek, Nina C.; Artibani, Mara; El-Sahhar, Salma; Sauka-Spengler, Tatjana; Yau, Christopher; Tresp, Volker und Ahmed, Ahmed A.
(2020):
A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes.
In: eLife, Bd. 9, e55207
[PDF, 1MB]
Trautmann, Dietrich; Fromm, Michael; Tresp, Volker; Seidl, Thomas und Schütze, Hinrich
(2020):
Relational and Fine-Grained Argument Mining. The LMU Munich project ReMLAV within the DFG Priority Program RATIO “Robust Argumentation Machines”.
In: Datenbank-Spektrum, Bd. 20, Nr. 2: S. 99-105
[PDF, 365kB]
2019
Ma, Yunpu; Tresp, Volker und Daxberger, Erik A.
(2019):
Embedding models for episodic knowledge graphs.
In: Journal of Web Semantics, Bd. 59, UNSP 100490
Bergs, Christoph; Khalil, Mohamed; Hildebrandt, Marcel; Heizmann, Michael; Wuechner, Roland; Bletzinger, Kai-Uwe und Tresp, Volker
(2019):
Health indication of electric motors using a hybrid modeling approach.
In: Tm-Technisches Messen, Bd. 86, Nr. 11: S. 640-650
Hildebrandt, Marcel; Sunder, Swathi Shyam; Mogoreanu, Serghei; Joblin, Mitchell; Mehta, Akhil; Thon, Ingo und Tresp, Volker
(2019):
A Recommender System for Complex Real-World Applications with Nonlinear Dependencies and Knowledge Graph Context.
In: Semantic Web, Eswc 2019, Bd. 11503: S. 179-193
Hildebrandt, Marcel; Khalil, Mohamed; Bergs, Christoph; Tresp, Volker; Wuechner, Roland; Bletzinger, Kai-Uwe und Heizmann, Michael
(2019):
Remaining Useful Life Estimation for Unknown Motors Using a Hybrid Modeling Approach.
In: 2019 Ieee 17Th International Conference on Industrial Informatics (Indin): S. 1327-1332
Gu, Jindong; Yang, Yinchong und Tresp, Volker
(2019):
Understanding Individual Decisions of CNNs via Contrastive Backpropagation.
In: Computer Vision - Accv 2018, Pt Iii, Bd. 11363: S. 119-134
2018
Rohm, Markus; Tresp, Volker; Müller, Michael; Kern, Christoph; Manakov, Ilja; Weiss, Maximilian; Sim, Dawn A.; Priglinger, Siegfried; Keane, Pearse A. und Kortüm, Karsten
(2018):
Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration.
In: Ophthalmology, Bd. 125, Nr. 7: S. 1028-1036
2016
Esteban, Cristóbal; Tresp, Volker; Yang, Yinchong; Baier, Stephan und Krompaß, Denis
(2016):
Predicting the Co-Evolution of Event and Knowledge Graphs.
19th International Conference on Information Fusion (FUSION), Heidelberg, Germany, 5-8 July 2016.
IEEE Computer Society. S. 98-105
Baier, Stephan; Krompass, Denis und Tresp, Volker
(2016):
Learning Representations for Discrete Sensor Networks using Tensor Decompositions.
2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Baden-Baden, Germany, 19-21 September 2016.
IEEE Computer Society. S. 84-89
Esteban, Cristóbal; Staeck, Oliver; Baier, Stephan; Yang, Yinchong und Tresp, Volker
(2016):
Predicting Clinical Events by Combining Static and Dynamic Information using Recurrent Neural Networks.
2016 IEEE International Conference on Healthcare Informatics (ICHI), Chicago, Illinois, USA, 4-7 October 2016.
IEEE Computer Society. S. 93-101
Tresp, Volker; Overhage, J. Marc; Bundschus, Markus; Rabizadeh, Shahrooz; Fasching, Peter A. und Yu, Shipeng
(2016):
Going Digital: A Survey on Digitalization and Large-Scale Data Analytics in Healthcare.
In: Proceedings of the Ieee, Bd. 104, Nr. 11: S. 2180-2206
Haykin, Simon; Tresp, Volker und Benediktsson, Jon Atli
(2016):
Big Data: Practical Applications.
In: Proceedings of the Ieee, Bd. 104, Nr. 11: S. 2082-2084
Nickel, Maximilian; Murphy, Kevin; Tresp, Volker und Gabrilovich, Evgeniy
(2016):
A Review of Relational Machine Learning for Knowledge Graphs.
In: Proceedings of the Ieee, Bd. 104, Nr. 1: S. 11-33
Yang, Yinchong; Esteban, Cristóbal und Tresp, Volker
(2016):
Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling.
In: Sack, Harald (Hrsg.):
The Semantic Web. Latest Advances and New Domains 13th International Conference, ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Proceedings. Theoretical Computer Science and General Issues, Bd. 9678. Cham: Springer. S. 199-213
2008
Bundschus, Markus; Dejori, Mathaeus; Stetter, Martin; Tresp, Volker und Kriegel, Hans-Peter
(2008):
Extraction of semantic biomedical relations from text using conditional random fields.
In: BMC Bioinformatics
9:207
[PDF, 465kB]