Neural Information Processing

Machine Learning

2022

Seidel, R., Jahn, N., Seo, S., Goerttler, T., & Obermayer, K. (2022). "NAPC: A Neural Algorithm for Automated Passenger Counting in Public Transport on a Privacy-Friendly Dataset" , IEEE Open Journal of Intelligent Transportation Systems , 3 , 33-44.
Goerttler, T., Müller, L., & Obermayer, K. (2022). "Representation Change in Model-Agnostic Meta-Learning" .

2021

Müller, L., Ploner, M., Goerttler, T., & Obermayer, K. (2021). "An Interactive Introduction to Model-Agnostic Meta-Learning" .
Goerttler, T., & Obermayer, K. (2021). "Exploring the Similarity of Representations in Model-Agnostic Meta-Learning" .

2019

Laschos, V., Obermayer, K., Shen, Y., & Stannat, W. (2019). "A Fenchel-Moreau-Rockafellar type theorem on the Kantorovich-Wasserstein space with applications in partially observable Markov decision processes" , Journal of Mathematical Analysis and Applications .
Trowitzsch I., , Schymura C., , Kolossa D., , & K., O. (2019). "Joining Sound Event Detection and Localization Through Spatial Segregation" , IEEE Trans. Audio Speech Language Proc. .

2018

Liu, C., Xie, S., Xie, X., Duan, X., Wang, W., & Obermayer, K. (2018). "Design of a Video Feedback SSVEP-BCI System for Car Control Based on the Improved MUSIC Method" , Proceedings of the IEEE 6th International Winter Conference on Brain-Computer Interfaces .

2017

Trowitzsch, , Mohr, , Kashef, , & Obermayer, K. (2017). "Robust Detection of Environmental Sounds in Binaural Auditory Scenes" , IEEE Transactions on Audio Speech and Language Processing , 25 (6), 1344-1356.

2016

Boehmer, W., Guo, R., & Obermayer, K. (2016). "Non-deterministic Policy Improvement Stabilizes Approximate Reinforcement Learning" , Proceedings of the 13th European Workshop on Reinforcement Learning .

2015

Seo, S., Mohr, J., Ningfei, L., Horn, A., & Obermayer, K. (2015, Jul.). "Incremental pairwise clustering for large proximity matrices" in 2015 International Joint Conference on Neural Networks (IJCNN) . 1-8.
Shelton, J. A., Sheikh, A. -., Bornschein, J., Sterne, P., & Lücke, J. (2015, May). "Nonlinear Spike-And-Slab Sparse Coding for Interpretable Image Encoding" , PLoS ONE , 10 , e0124088. Public Library of Science .
[English] Hutter, F., Lücke, J., & Schmidt-Thieme, L. (2015). "Beyond Manual Tuning of Hyperparameters" , KI - Künstliche Intelligenz , 29 (4), 329-337. Springer Berlin Heidelberg .
Böhmer, W., Springenberg, J. T., Boedecker, J., Riedmiller, M., & Obermayer, K. (2015). "Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations" in Künstliche Intelligenz , Springer Berlin Heidelberg , 353-362.
Böhmer, W., & Obermayer, K. (2015). "Regression with Linear Factored Functions" in Machine Learning and Knowledge Discovery in Databases , Springer International Publishing , 119-134.
ISBN
978-3-319-23527-1, 978-3-319-23528-8

2014

Mohr, J., Seo, S., & Obermayer, K. (2014, Jul.). "A classifier-based association test for imbalanced data derived from prediction theory" in Neural Networks (IJCNN), 2014 International Joint Conference on . 487-493.
Svensson, C. -., Krusekopf, S., Lücke, J., & Figge, M. T. (2014, Apr.). "Automated Detection of Circulating Tumour Cells With Naive Bayesian Classifiers" , Cytometry Part A , 85 (6), 501–511.
Sheikh, A. -., Shelton, J. A., & Lücke, J. (2014). "A Truncated EM Approach for Spike-and-Slab Sparse Coding" , Journal of Machine Learning Research , 15 , 2653–2687.
Dai, Z., & Lücke, J. (2014). "Autonomous Document Cleaning – A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts" , IEEE Transactions on Pattern Analysis and Machine Intelligence , 36 (10), 1950–1962.
Henniges, M., Turner, R. E., Sahani, M., Eggert, J., & Lücke, J. (2014). "Efficient Occlusive Components Analysis" , Journal of Machine Learning Research , 15 , 2689–2722.
Tobia, M. J., Guo, R., Schwarze, U., Böhmer, W., Gläscher, J., Finckh, B., Marschner, A., Büchel, C., Obermayer, K., & Sommer, T. (2014). "Neural Systems for Choice and Valuation with Counterfactual Learning Signals" , NeuroImage , 89 , 57-69. Elsevier .
ISBN
978-3-319-23527-1, 978-3-319-23528-8