talks

  • [t21] Lukas Galke (2023, May 17). Uncovering Patterns in Medical Literature through Lifelong Automated Categorization and Research Dynamics Analysis with Machine Learning [upcoming talk]. KIK AI Coffee & Learning meeting, Amsterdam, The Netherlands.

  • [t20] Lukas Galke (2023, May 16). What makes a language easy to deep learn? [upcoming talk]. Computational Linguistics Seminar, University of Amsterdam, The Netherlands.

  • [t19] Lukas Galke (2023, February 27). What makes a language easy to deep learn? [paper presentation]. Language Evolution and Emergence meeting, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

  • [t18] Lukas Galke (2022, October 20). Structure in Language Learning Systems [informal talk]. TALEP Marseille, online.

  • [t17] Lukas Galke (2022, September 5). Machine Learning for Language Evolution – What’s missing? [workshop presentation]. Machine Learning and the Evolution of Language (ml4evolang) workshop at JCOLE’22, Japan/online.

  • [t16] Lukas Galke (2022, August 28). Representation Learning for Texts and Graphs [viva]. Department of Computer Science, Kiel University, Germany.

  • [t15] Lukas Galke (2022, August 18). Language Technology [workshop]. Regiodag 2022 Probusclubs Nijmegen e.o., Nijmegen, The Netherlands.

  • [t14] Lukas Galke (2022, July 19). General Cross-Architecture Distillation of Pretrained Language Models into Matrix Embeddings [oral presentation]. World Congress on Computational Intelligence, Padua, Italy.

  • [t13] Lukas Galke (2022, June 1). Emergent Communication for Understanding Human Language Evolution: What’s missing? [poster presentation]. IMPRS conference, Nijmegen, The Netherlands.

  • [t12] Lukas Galke (2022, April 29). Emergent Communication for Understanding Human Language Evolution [discussion session]. EmeCom workshop at ICLR’22, online.

  • [t11] Lukas Galke (2021, December 15). COVID-19++: A Citation-Aware Covid-19 Dataset for the Analysis of Research Dynamics [oral presentation]. 2021 IEEE International Conference on Big Data (Big Data), online.

  • [t10] Lukas Galke (2021, July 18). Lifelong learning of graph neural networks for open-world node classification [oral presentation]. International Joint Conference on Neural Networks, online.

  • [t9] Lukas Galke (2020, June 23). Scaling Up Graph Neural Networks [oral presentation], Graph Neural Network Reading Group, online.

  • [t8] Lukas Galke (2019, September 26). Inductive Learning of Concept Representations from Library-Scale Corpora with Graph Convolution [oral presentation], INFORMATIK 2019, Kassel, Germany.

  • [t7] Lukas Galke (2019, September 26). What If We Encoded Words as Matrices and Used Matrix Multiplication as Composition Function [oral presentation]. INFORMATIK 2019, Kassel, Germany

  • [t6] Lukas Galke, Florian Mai (2019, May 8). CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model [poster presentation]. International Conference on Learning Representations, New Orleans, Lousiana.

  • [t5] Lukas Galke (2019, May 7). Can Graph Neural Networks Go Online? An Analysis of Pretraining and Inference [poster presentation]. International Conference on Learning Representations, New Orleans, Lousiana.

  • [t4] Lukas Galke (2018, July 10). Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels [oral presentation]. Conference on User Modeling, Adaptation and Personalization, Singapore, Singapore.

  • [t3] Lukas Galke (2017, December 6). Using Titles vs. Full-text as Source for Automated Semantic Document Annotation [oral presentation], Knowledge Capture Conference, Austin, Texas.

  • [t2] Lukas Galke (2017, September 28). Reranking-based Recommender Systems with Deep Learning [oral presentation]. INFORMATIK 2017, Chemnitz, Germany.

  • [t1] Lukas Galke (2017, September 28). Word Embeddings for Practical Information Retrieval [oral presentation]. INFORMATIK 2017, Chemnitz, Germany.