Prof. Dr. Christian Bauckhage

Christian Bauckhage ist Professor für Informatik (Mustererkennung) an der Universität Bonn und Lead Scientist für Maschinelles Lernen am Fraunhofer IAIS. Nach erfolgreicher Promotion in Informatik an der Universität Bielefeld arbeitete er zunächst als PostDoc am Centre for Vision Research in Toronto und anschließend als Senior Research Scientist bei den Deutsche Telekom Laboratories in Berlin, bevor er 2008 nach Bonn berufen wurde. Seine Erfahrung im Bereich Data Science und Künstliche Intelligenz erstreckt sich bereits über mehr als 20 Jahre und begründet seine Rolle als renommierten KI-Experte und Referent auf Veranstaltungen, Messen und Tagungen. Aktuell befasst sich Prof. Bauckhage vor allem mit dem Thema Quantencomputing und den durch Quantencomputern entstehenden Möglichkeiten, bisher nahezu unlösbare Verfahren der Künstlichen Intelligenz und des Maschinellen Lernens zu erschließen.

Jahr
Year
Titel/Autor:in
Title/Author
Publikationstyp
Publication Type
2021 ALiBERT: Improved automated list inspection (ALI) with BERT
Ramamurthy, R.; Pielka, M.; Stenzel, R.; Bauckhage, C.; Sifa, R.; Khameneh, T.D.; Warning, U.; Kliem, B.; Loitz, R.
Konferenzbeitrag
Conference Paper
2021 An Optimization for Convolutional Network Layers Using the Viola-Jones Framework and Ternary Weight Networks
Agombar, R.; Bauckhage, C.; Luebbering, M.; Sifa, R.
Konferenzbeitrag
Conference Paper
2021 Anonymization of German financial documents using neural network-based language models with contextual word representations
Biesner, David; Ramamurthy, Rajkumar; Stenzel, Robin; Lübbering, Max; Hillebrand, Lars Patrick; Ladi, Anna; Pielka, Maren; Loitz, Rüdiger; Bauckhage, Christian; Sifa, Rafet
Zeitschriftenaufsatz
Journal Article
2021 Auto Encoding Explanatory Examples with Stochastic Paths
Ojeda, César; Sánchez, Ramsés J.; Cvejoski, Kostadin; Schücker, Jannis; Bauckhage, Christian; Georgiev, Bogdan
Konferenzbeitrag
Conference Paper
2021 Automatic Indexing of Financial Documents via Information Extraction
Ramamurthy, Rajkumar; Lübbering, Max; Bell , Thiago; Gebauer, Michael; Ulusay, Bilge; Uedelhoven, Daniel; Dilmaghani, Tim; Loitz, Rüdiger; Pielka, Maren; Bauckhage, Christian; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2021 Decision Snippet Features
Welke, Pascal; Alkhoury, Fouad; Bauckhage, Christian; Wrobel, Stefan
Konferenzbeitrag
Conference Paper
2021 Decoupling Autoencoders for Robust One-vs-Rest Classification
Lübbering, Max; Gebauer, Michael; Ramamurthy, Rajkumar; Bauckhage, Christian; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2021 Grundlagen des Maschinellen Lernens
Bauckhage, Christian; Hübner, Wolfgang; Hug, Ronny; Paaß, Gerhard; Rüping, Stefan
Aufsatz in Buch
Book Article
2021 Learning Deep Generative Models for Queuing Systems
Ojeda, César; Cvejoski, Kostadin; Georgiev, Bogdan; Bauckhage, Christian; Schuecker, Jannis; Sánchez, Ramsés J.
Konferenzbeitrag
Conference Paper
2021 Performance of ECG-based seizure detection algorithms strongly depends on training and test conditions
Jahanbekam, A.; Baumann, J.; Nass, R.D.; Bauckhage, C.; Hill, H.; Elger, C.E.; Surges, R.
Zeitschriftenaufsatz
Journal Article
2021 Street-Map Based Validation of Semantic Segmentation in Autonomous Driving
Rüden, Laura von; Wirtz, Tim; Hueger, Fabian; Schneider, Jan David; Piatkowski, Nico; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2021 Supervised autoencoder variants for end to end anomaly detection
Lübbering, M.; Gebauer, M.; Ramamurthy, R.; Sifa, R.; Bauckhage, C.
Konferenzbeitrag
Conference Paper
2021 Switching Dynamical Systems with Deep Neural Networks
Ojeda, César; Georgiev, Bogdan; Cvejoski, Kostadin; Schücker, Jannis; Bauckhage, Christian; Sánchez, Ramsés J.
Konferenzbeitrag
Conference Paper
2021 Tackling Contradiction Detection in German Using Machine Translation and End-to-End Recurrent Neural Networks
Pielka, Maren; Sifa, Rafet; Hillebrand, Lars Patrick; Biesner, David; Ramamurthy, Rajkumar; Ladi, Anna; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2021 tanh Neurons are Bayesian Decision Makers
Bauckhage, Christian; Sifa, Rafet; Hecker, Dirk
Konferenzbeitrag
Conference Paper
2021 Tiefe neuronale Netze
Bauckhage, Christian; Hübner, Wolfgang; Hug, Ronny; Paaß, G.
Aufsatz in Buch
Book Article
2021 Towards Intelligent Food Waste Prevention: An Approach Using Scalable and Flexible Harvest Schedule Optimization with Evolutionary Algorithms
Günder, Maurice; Piatkowski, Nico; Rüden, Laura von; Sifa, Rafet; Bauckhage, Christian
Zeitschriftenaufsatz
Journal Article
2021 Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis
Lübbering, Max; Pielka, Maren; Das, Kajaree; Gebauer, Michael; Ramamurthy, Rajkumar; Bauckhage, Christian; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2021 Utilizing Representation Learning for Robust Text Classification Under Datasetshift
Lübbering, Max; Gebauer, Michael; Ramamurthy, Rajkumar; Pielka, Maren; Bauckhage, Christian; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2021 Vertrauenswürdiges, transparentes und robustes Maschinelles Lernen
Bauckhage, Christian; Fürnkranz, Johannes; Paaß, Gerhard
Aufsatz in Buch
Book Article
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica
Jahr
Year
Titel/Autor:in
Title/Author
Publikationstyp
Publication Type
2020 A Community Detection Based Approach for Exploring Patterns in Player Reviews
Pielka, Maren; Sifa, Rafet; Ramamurthy, Rajkumar; Ojeda, César; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 Adiabatic Quantum Computing for Max-Sum Diversification
Bauckhage, Christian; Sifa, Rafet; Wrobel, Stefan
Konferenzbeitrag
Conference Paper
2020 Combining Machine Learning and Simulation to a Hybrid Modelling Approach: Current and Future Directions
Rüden, Laura von; Mayer, Sebastian; Sifa, Rafet; Bauckhage, Christian; Garcke, Jochen
Konferenzbeitrag
Conference Paper
2020 Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents
Pielka, Maren; Ladi, Anna; Chapman, Clayton; Brito, Eduardo; Ramamurthy, Rajkumar; Mayer, Paul; Wahab, Abdul; Sifa, Rafet; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 From Imbalanced Classification to Supervised Outlier Detection Problems: Adversarially Trained Auto Encoders
Lübbering, Max; Ramamurthy, Rajkumar; Gebauer, Michael; Bell, Thiago; Sifa, Rafet; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 Guided Reinforcement Learning via Sequence Learning
Ramamurthy, Rajkumar; Sifa, Rafet; Lübbering, Max; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 Hopfield Networks for Vector Quantization
Bauckhage, Christian; Ramamurthy, Rajkumar; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2020 Informed Machine Learning - A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Rüden, Laura von; Mayer, Sebastian; Beckh, Katharina; Georgiev, Bogdan; Giesselbach, Sven; Heese, Raoul; Kirsch, Birgit; Pfrommer, Julius; Pick, Annika; Ramamurthy, Rajkumar; Walczak, Michal; Garcke, Jochen; Bauckhage, Christian; Schuecker, Jannis
Paper
2020 Interpretable Topic Extraction and Word Embedding Learning Using Row-Stochastic DEDICOM
Hillebrand, L.; Biesner, D.; Bauckhage, C.; Sifa, R.
Konferenzbeitrag
Conference Paper
2020 Leveraging Contextual Text Representations for Anonymizing German Financial Documents
Biesner, David; Ramamurthy, Rajkumar; Lübbering, Max; Fürst, Benedikt; Ismail, H.; Hillebrand, L.; Ladi, A.; Pielka, M.; Stenzel, R.; Khameneh, T.; Krapp, V.; Huseynov, I.; Schlums, J.; Stoll, U.; Warning, U.; Kliem, B.; Bauckhage, C.; Sifa, R.
Konferenzbeitrag
Conference Paper
2020 Matrix- and Tensor Factorization for Game Content Recommendation
Sifa, Rafet; Yawar, Raheel; Ramamurthy, Rajkumar; Bauckhage, Christian; Kersting, Kristian
Zeitschriftenaufsatz
Journal Article
2020 Novelty Discovery with Kernel Minimum Enclosing Balls
Sifa, Rafet; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 Novelty-Guided Reinforcement Learning via Encoded Behaviors
Ramamurthy, R.; Sifa, R.; Lübbering, M.; Bauckhage, C.
Konferenzbeitrag
Conference Paper
2020 Patterns and Outliers in Temporal Point Processes
Ojeda, César; Cvejoski, Kostadin; Sifa, Rafet; Schücker, Jannis; Bauckhage, Christian
Konferenzbeitrag
Conference Paper
2020 Problem Solving with Hopfield Networks and Adiabatic Quantum Computing
Bauckhage, C.; Sanchez, R.; Sifa, R.
Konferenzbeitrag
Conference Paper
2020 Quantum Machine Learning. Eine Analyse zu Kompetenz, Forschung und Anwendung
Bauckhage, Christian; Brito, Eduardo; Daase, Inga; Franken, Lukas; Georgiev, Bogdan; Hecker, Dirk; Paschke, Adrian; Piatkowski, Nico; Soddemann, Thomas; Trabold, Daniel
Studie
Study
2020 Recurrent Point Review Models
Cvejoski, K.; Sanchez, R.J.; Georgiev, B.; Bauckhage, C.; Ojeda, C.
Konferenzbeitrag
Conference Paper
2020 Shells within Minimum Enclosing Balls
Bauckhage, Christian; Bortz, Michael; Sifa, Rafet
Konferenzbeitrag
Conference Paper
2020 Towards Map-Based Validation of Semantic Segmentation Masks
Rüden, Laura von; Wirtz, Tim; Hueger, Fabian; Schneider, Jan David; Bauckhage, Christian
Vortrag
Presentation
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica

C. Bauckhage and R. Sifa. Joint Selection of Central and Extremal Prototypes Based on Kernel Minimum Enclosing Balls, Proc. IEEE Int. Conf.  on  Data Science and Advanced Analytics, 2019

C. Bauckhage, R. Sifa, and T. Dong. Prototypes within Minimum Enclosing Balls, Proc. Int. Conf on Artificial Neural Networks, 2019

T. Dong, Z. Wang, J. Li, C. Bauckhage, and A.B. Cremers. Triple Classification Using Regions and Fine-grained Entity Typing, Proc. AAAI Conf. on Artificial Intelligence, 2019

C. Bauckhage, E. Brito, K. Cvejoski, C. Ojeda, J. Schücker, and R. Sifa. Towards Shortest Paths Via Adiabatic Quantum Computing. Proc. Mining and Learning with Graphs, 2018

B. Wulff, J. Schücker, and C. Bauckhage. SPSA for Layer-wise Training of Deep Networks, Proc. Int. Conf on Artificial Neural Networks, 2018

R. Sifa and C. Bauckhage. Online k-Maxoids Clustering. Proc. IEEE Int. Conf.  on  Data Science and Advanced Analytics,  2017
 
C. Bauckhage. A Neural Network Implementation of Frank-Wolfe Optimization. Proc. Int. Conf on Artificial Neural Networks, 2017
 
R. Ramamurthy, C. Bauckhage, K. Buza, and S. Wrobel. Using Echo State Networks for Cryptography. Proc. Int. Conf on Artificial Neural Networks, 2017
 
C. Ojeda, K. Cvejoski, R. Sifa, C. Bauckhage. Inverse Dynamical Inheritance in Stack Exchange Taxonomies. Proc. AAAI Int. Conf. on Web and Social media, 2017

C. Bauckhage and K. Kersting. Collective Attention on the Web. Foundations and Trends in Web Science 5(1-2), 2016

M. Neumann, R. Garnett, C. Bauckhage, and K. Kersting. Propagation kernels: efficient graph kernels from propagated information. Machine Learning 102(2), 2016

M. Höhne, A. Jahanbekam, C. Bauckhage, N. Axmacher, and J. Fell. Prediction of successful memory encoding based on single-trial rhinal and hippocampal phase information. NeuroImage 139, 2016

S. Zhang, D.A. Klein, C. Bauckhage, and A.B. Cremers. Fast Moving Pedestrian Detection Based on Motion Segmentation and New Motion Features. Multimedia Tools and Applications, 2015

S. Zhang, C. Bauckhage, and A.B. Cremers. Efficient Pedestrian Detection via Rectangular Features Based on a Statistical Shape Model. IEEE Trans. Intelligent Transportation Systems, 16(2), 2015

C. Bauckhage, F. Hadiji, and K. Kersting. How Viral Are Viral Videos?. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2015

C. Bauckhage, K. Kersting, and B. Rastegarpanah. Collective Attention to Social Media Evolves According to Diffusion Models. Proc. ACM Int. World Wide Web Conf., 2014

C. Bauckhage and K. Manshaei. Kernel Archetypal Analysis for Clustering Web Search Frequency Time Series. Proc. IAPR Int. Conf. on Pattern Recognition, IEEE, 2014

C. Bauckhage, K. Kersting, and F. Hadiji. Mathematical Models of Fads Explain the Temporal Dynamics of Internet Memes. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2013

C. Bauckhage and K. Kersting. Can Computers Learn from the Aesthetic Wisdom of the Crowd? KI - Künstliche Intelligenz, 27(1), 2013

C. Bauckhage and K. Kersting. Data Mining and Pattern Recognition in Agriculture. KI - Künstliche Intelligenz, 27(4), 2013

G. Evangelidis and C. Bauckhage. Efficient Subframe Video Alignment using Short Descriptors. IEEE Trans. Pattern Analysis and Machine Intelligence, 35(10), 2013

C. Bauckhage, K. Kersting, and A. Schmit. Agriculture's Technological Makeover. IEEE Pervasive Computing, 11(2), 2012

C. Thurau, K. Kersting, M. Wahabzada, and C. Bauckhage. Descriptive Matrix Factorization for Sustainability: Adopting the Principle of Opposites. Data Mining and Knowledge Discovery, 24(2), 2012

B. Krausz and C. Bauckhage. Loveparade 2010: Automatic video analysis of a crowd disaster. Computer Vision and Image Understanding, 116(3), 2012

C. Bauckhage. Insights into Internet Memes. Proc. AAAI Int. Conf. on Weblogs and Social Media, 2011

C. Thurau, K. Kersting, M. Wahabzada, and C. Bauckhage. Convex Non-negative Matrix Factorization for Massive Datasets. Knowledge and Information Systems, 29(2), 2011

C. Thurau, K. Kersting, and C. Bauckhage. Yes We Can: Simplex Volume Maximization for Descriptive Web-scale Matrix Factorization. Proc. ACM Conf. on Information and Knowledge Management, 2010

R. Wetzker, C. Zimmermann, C. Bauckhage, and S. Albayrak. I Tag, You Tag: Translating Tags for Advanced User Models. Proc. ACM Int. Conf. on Web Search and Data Mining, 2010

C. Bauckhage and C. Thurau. Making Archetypal Analysis Practical, Proc. DAGM Symposium, 2009

J. Kunegis, A. Lommatzsch, and C. Bauckhage. The Slashdot Zoo: Mining a Social Network with Negative Edges. Proc. ACM Int. World Wide Web Conf., 2009

C. Bauckhage, J.K. Tsotsos, and F.E. Bunn. Automatic Detection of Abnormal Gait. Image and Vision Computing, 27(1-2), 2009