Patrick Seifner

According to our database, Patrick Seifner authored at least 10 papers between 2023 and 2026.

Collaborative distances:

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

2026

Foundation Inference Models for Ordinary Differential Equations.

Maximilian Mauel, Johannes R. Hübers, David Berghaus, Patrick Seifner, Ramsés J. Sánchez

CoRR, February, 2026

2025

Towards Foundation Inference Models that Learn ODEs In-Context.

Maximilian Mauel, Manuel Hinz, Patrick Seifner, David Berghaus, Ramsés J. Sánchez

CoRR, October, 2025

On Foundation Models for Temporal Point Processes to Accelerate Scientific Discovery.

David Berghaus, Patrick Seifner, Kostadin Cvejoski, Ramsés J. Sánchez

CoRR, October, 2025

Towards Fast Coarse-graining and Equation Discovery with Foundation Inference Models.

Manuel Hinz, Maximilian Mauel, Patrick Seifner, David Berghaus, Kostadin Cvejoski, Ramsés J. Sánchez

CoRR, October, 2025

In-Context Learning of Temporal Point Processes with Foundation Inference Models.

David Berghaus, Patrick Seifner, Kostadin Cvejoski, César Ojeda, Ramsés J. Sánchez

CoRR, September, 2025

Foundation Inference Models for Stochastic Differential Equations: A Transformer-based Approach for Zero-shot Function Estimation.

Patrick Seifner, Kostadin Cvejoski, David Berghaus, César Ojeda, Ramsés J. Sánchez

CoRR, February, 2025

Zero-shot Imputation with Foundation Inference Models for Dynamical Systems.

Patrick Seifner, Kostadin Cvejoski, Antonia Körner, Ramsés J. Sánchez

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Foundational Inference Models for Dynamical Systems.

Patrick Seifner, Kostadin Cvejoski, Ramsés J. Sánchez

CoRR, 2024

Foundation Inference Models for Markov Jump Processes.

David Berghaus, Kostadin Cvejoski, Patrick Seifner, César Ali Marin Ojeda, Ramsés J. Sánchez

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Neural Markov Jump Processes.

Patrick Seifner, Ramsés J. Sánchez

Proceedings of the International Conference on Machine Learning, 2023