| Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research T Koopmann, M Stubbemann, M Kapa, M Paris, G Buenstorf, T Hanika, ... Scientometrics, 1-22, 2021 | 19 | 2021 |
| FCA2VEC: Embedding Techniques for Formal Concept Analysis D Dürrschnabel, T Hanika, M Stubbemann Complex Data Analytics with Formal Concept Analysis, 47-74, 2021 | 13 | 2021 |
| Intrinsic dimension for large-scale geometric learning M Stubbemann, T Hanika, FM Schneider arXiv preprint arXiv:2210.05301, 2022 | 6 | 2022 |
| Orometric methods in bounded metric data M Stubbemann, T Hanika, G Stumme International Symposium on Intelligent Data Analysis, 496-508, 2020 | 5 | 2020 |
| Lg4av: Combining language models and graph neural networks for author verification M Stubbemann, G Stumme International Symposium on Intelligent Data Analysis, 315-326, 2022 | 4 | 2022 |
| Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training J Burchert, T Werner, VK Yalavarthi, DC de Portugal, M Stubbemann, ... arXiv preprint arXiv:2404.06966, 2024 | 3 | 2024 |
| Moco: A learnable meta optimizer for combinatorial optimization T Dernedde, D Thyssens, S Dittrich, M Stubbemann, L Schmidt-Thieme arXiv preprint arXiv:2402.04915, 2024 | 3 | 2024 |
| The mont blanc of twitter: Identifying hierarchies of outstanding peaks in social networks M Stubbemann, G Stumme Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 2 | 2023 |
| Selecting Features by their Resilience to the Curse of Dimensionality M Stubbemann, T Hille, T Hanika arXiv preprint arXiv:2304.02455, 2023 | 2 | 2023 |
| Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting C Klötergens, VK Yalavarthi, M Stubbemann, L Schmidt-Thieme Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | | 2024 |
| A Cross-Domain Benchmark for Active Learning T Werner, J Burchert, M Stubbemann, L Schmidt-Thieme arXiv preprint arXiv:2408.00426, 2024 | | 2024 |
| Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research T Hille, M Stubbemann, T Hanika arXiv preprint arXiv:2403.08438, 2024 | | 2024 |
| ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing K Madhusudhanan, G Behrens, M Stubbemann, L Schmidt-Thieme arXiv preprint arXiv:2403.03812, 2024 | | 2024 |
| Orometry, Intrinsic Dimensionality and Learning: Novel Insights into Network Data M Stubbemann | | 2023 |
| Robust EEG Classification via Graph Neural Networks N Ahmed, J Burchert, VK Yalavarthi, M Stubbemann, L Schmidt-Thieme | | |
Tom HanikaInstitute of Computer Science, University of HildesheimZweryfikowany adres z uni-hildesheim.de
