Damrich, Sebastian

11 publications

TMLR 2026 DREAMS: Preserving Both Local and Global Structure in Dimensionality Reduction Noël Kury, Dmitry Kobak, Sebastian Damrich

TMLR 2025 Node Embeddings via Neighbor Embeddings Jan Niklas Böhm, Marius Keute, Alica Guzmán, Sebastian Damrich, Andrew Draganov, Dmitry Kobak

ICML 2025 On the Importance of Embedding Norms in Self-Supervised Learning Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J Bekkers

NeurIPS 2025 TRACE: Contrastive Learning for Multi-Trial Time Series Data in Neuroscience Lisa Schmors, Dominic Gonschorek, Jan Niklas Böhm, Yongrong Qiu, Na Zhou, Dmitry Kobak, Andreas S. Tolias, Fabian H. Sinz, Jacob Reimer, Katrin Franke, Sebastian Damrich, Philipp Berens

NeurIPS 2024 Persistent Homology for High-Dimensional Data Based on Spectral Methods Sebastian Damrich, Philipp Berens, Dmitry Kobak

ICLR 2023 From $t$-SNE to UMAP with Contrastive Learning Sebastian Damrich, Niklas Böhm, Fred A Hamprecht, Dmitry Kobak

ICML 2023 Geometric Autoencoders - What You See Is What You Decode Philipp Nazari, Sebastian Damrich, Fred A Hamprecht

ICML 2022 The Algebraic Path Problem for Graph Metrics Enrique Fita Sanmartı́n, Sebastian Damrich, Fred Hamprecht

NeurIPS 2021 Directed Probabilistic Watershed Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht

NeurIPS 2021 On UMAP's True Loss Function Sebastian Damrich, Fred A. Hamprecht

NeurIPS 2019 Probabilistic Watershed: Sampling All Spanning Forests for Seeded Segmentation and Semi-Supervised Learning Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht