Real-Time Dense Geometry from a Handheld Camera. - Jan Stühmer; Stefan Gumhold; Daniel Cremers (DAGM-Symposium, 2010)

Parallel Generalized Thresholding Scheme for Live Dense Geometry from a Handheld Camera. - Jan Stühmer; Stefan Gumhold; Daniel Cremers (ECCV Workshops (1), 2010)

Tree Shape Priors with Connectivity Constraints Using Convex Relaxation on General Graphs. - Jan Stühmer; Peter Schröder; Daniel Cremers (ICCV, 2013)

Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes. - Rudolph Triebel; Jan Stühmer; Mohamed Souiai; Daniel Cremers (GCPR, 2014)

Generalized Connectivity Constraints for Spatio-temporal 3D Reconstruction. - Martin Ralf Oswald; Jan Stühmer; Daniel Cremers (ECCV (4), 2014)

A Fast Projection Method for Connectivity Constraints in Image Segmentation. - Jan Stühmer; Daniel Cremers (EMMCVPR, 2014)

Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations. - Jan Stühmer; Sebastian Nowozin; Andrew W. Fitzgibbon; Richard Szeliski; Travis Perry; Sunil Acharya; Daniel Cremers; Jamie Shotton (ICCV, 2015)

A Convex Optimization Framework for Connectivity Constraints in Image Segmentation and 3D Reconstruction. - Jan Stühmer (2016)

Variational Inference for Data-Efficient Model Learning in POMDPs. - Sebastian Tschiatschek; Kai Arulkumaran; Jan Stühmer; Katja Hofmann (CoRR, 2018)

Disentangling Interpretable Generative Parameters of Random and Real-World Graphs. - Niklas Stoehr; Marc Brockschmidt; Jan Stuehmer; Emine Yilmaz (CoRR, 2019)

Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. - Jan Stuehmer; Richard E. Turner; Sebastian Nowozin (AISTATS, 2020)

HoloLens 2 Research Mode as a Tool for Computer Vision Research. - Dorin Ungureanu; Federica Bogo; Silvano Galliani; Pooja Sama; Xin Duan; Casey Meekhof; Jan Stühmer; Thomas J. Cashman 001; Bugra Tekin; Johannes L. Schönberger; Pawel Olszta; Marc Pollefeys (CoRR, 2020)

H2O: Two Hands Manipulating Objects for First Person Interaction Recognition. - Taein Kwon; Bugra Tekin; Jan Stühmer; Federica Bogo; Marc Pollefeys (ICCV, 2021)

Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. - Shell Xu Hu; Da Li 001; Jan Stühmer; Minyoung Kim 001; Timothy M. Hospedales (CVPR, 2022)

HyperInvariances: Amortizing Invariance Learning. - Ruchika Chavhan; Henry Gouk; Jan Stühmer; Timothy M. Hospedales (CoRR, 2022)

Amortised Invariance Learning for Contrastive Self-Supervision. - Ruchika Chavhan; Jan Stuehmer; Calum Heggan; Mehrdad Yaghoobi; Timothy M. Hospedales (ICLR, 2023)

Learning Where and When to Reason in Neuro-Symbolic Inference. - Cristina Cornelio; Jan Stühmer; Shell Xu Hu; Timothy M. Hospedales (NeSy, 2023)

Amortised Invariance Learning for Contrastive Self-Supervision. - Ruchika Chavhan; Henry Gouk; Jan Stuehmer; Calum Heggan; Mehrdad Yaghoobi; Timothy M. Hospedales (CoRR, 2023)

Connectivity Optimized Nested Graph Networks for Crystal Structures. - Robin Ruff; Patrick Reiser; Jan Stühmer; Pascal Friederich (CoRR, 2023)

Generating Highly Designable Proteins with Geometric Algebra Flow Matching. - Simon Wagner; Leif Seute; Vsevolod Viliuga; Nicolas Wolf; Frauke Gräter; Jan Stühmer (NeurIPS, 2024)

Grappa - A Machine Learned Molecular Mechanics Force Field. - Leif Seute; Eric Hartmann; Jan Stühmer; Frauke Gräter (CoRR, 2024)

Graph Neural Networks and Spatial Information Learning for Post-Processing Ensemble Weather Forecasts. - Moritz Feik; Sebastian Lerch; Jan Stühmer (CoRR, 2024)

Machine Learning and AI in the Sciences. - Jan Stühmer (Künstliche Intell., 2024)

Learning conformational ensembles of proteins based on backbone geometry. - Nicolas Wolf; Leif Seute; Vsevolod Viliuga; Simon Wagner; Jan Stühmer; Frauke Gräter (CoRR, 2025)

Set-LLM: A Permutation-Invariant LLM. - Beni Egressy; Jan Stühmer (CoRR, 2025)

Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning. - Torben Berndt; Benjamin Walker 001; Tiexin Qin; Jan Stühmer; Andrey Kormilitzin (CoRR, 2025)