Jan Niklas Böhm

According to our database, Jan Niklas Böhm authored at least 9 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Node Embeddings via Neighbor Embeddings.

Jan Niklas Böhm, Marius Keute, Alica Guzmán, Sebastian Damrich, Andrew Draganov, Dmitry Kobak

Trans. Mach. Learn. Res., 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Self-supervised Visualisation of Medical Image Datasets.

Ifeoma Veronica Nwabufo, Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

CoRR, 2024

2023

From $t$-SNE to UMAP with contrastive learning.

Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised visualization of image datasets using contrastive learning.

Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Attraction-Repulsion Spectrum in Neighbor Embeddings.

Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

J. Mach. Learn. Res., 2022

Contrastive learning unifies t-SNE and UMAP.

Sebastian Damrich, Jan Niklas Böhm, Fred A. Hamprecht, Dmitry Kobak

CoRR, 2022

2020

A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum.

Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

CoRR, 2020