Marten Lienen
I care about solving problems and improving efficiency with software and machine learning. Aesthetically pleasing code makes me extra happy. At the moment, I am a postdoc at Helmholtz Munich, where I work on protein generation. Before that, I did a PhD at TUM’s DAML group where I worked on time series and generative models. Even further back, I worked on 3D object detection for autonomous driving at BMW.
On my computing devices, I enjoy software that empowers the user through extensibility and introspection as Linux and Emacs do. This goes hand in hand with an affinity for digital sovereignty, self-hosting and data ownership through software like Forgejo. Stumbling upon an unfamiliar programming language in the wild like Janet is also sure to pique my interest.
Find me on github, mastodon, scholar or subscribe to my rss feed.
Writing
- What is dϐ in an SDE?
- 80/20 LaTeX Snippets to Polish Your Papers
- Gaussian Processes are Bayesian Linear Regression
- Research Advice for Myself
- Uniform Edge Sampling from Complete k-Partite Graphs
- Starting a User Service on Suspend
- From Jekyll to Nikola
- Installing CyanogenMod on a Samsung Galaxy S4
- Writing a Research Paper
Publications
Edit-Based Flow Matching for Temporal Point Processes International Conference on Learning Representations, 2026Discrete Bayesian Sample Inference for Graph Generation International Conference on Learning Representations, 2026Generative Modeling with Bayesian Sample Inference Preprint, 2025UnHiPPO: Uncertainty-aware Initialization for State Space Models International Conference on Machine Learning, 2025Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting International Conference on Learning Representations, 2025Assessing Robustness via Score-Based Adversarial Image Generation Transactions on Machine Learning Research, 2025Unfolding Time: Generative Modeling for Turbulent Flows in 4D AI4Science Workshop, ICML, 2024From Zero to Turbulence: Generative Modeling for 3D Flow Simulation International Conference on Learning Representations, 2024Add and Thin: Diffusion for Temporal Point Processes Neural Information Processing Systems, 2023torchode: A Parallel ODE Solver for PyTorch The Symbiosis of Deep Learning and Differential Equations Workshop, NeurIPS, 2022Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks International Conference on Learning Representations, 2022 (Spotlight)Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More International Conference on Machine Learning, 2021 (Spotlight)FLGR: Fixed Length Gists Representation Learning for RNN-HMM Hybrid-based Neuromorphic Continuous Gesture Recognition Frontiers in Neuroscience, 13, 2019Rate-Adaptive Link Quality Estimation for Coded Packet Networks IEEE 41st Conference on Local Computer Networks, 2016