Marvin Sextro
@marvinsxtrMachine Learning for Precision Medicine | PhD Student at BIFOLD & TU Berlin | Data Scientist at Aignostics
Language Breakdown
Lines of code distribution across 12 owned repositories
I-Shaped Developer
I-shapedSpecialist — deep expertise in Jupyter Notebook
Collaboration Network
Global Impact visualization
Repos
75
PRs
0
Growth
+18%
Top Collaborators
No collaborator data yet.
Coding Streak
Contribution activity over the past year
grpinto
@grpinto
SauersML
@SauersML
Mariana
@marianaw
binru33
@binru33
David Holzmüller
@dholzmueller
Top Repositories
Template machine learning project using wandb, hydra-zen and submitit on Slurm with Apptainer
MapPFN: Learning Causal Perturbation Maps in Context
Code and experiments of the Explainable Cell Graphs (xCG) paper
2D Flow Matching in JAX with equinox and diffrax
Minimal implementation of D-Flow: Differentiating through Flows for Controlled Generation
Self-maintaining research wiki in Obsidian pulling from Zotero and Scholar Inbox, managed by Claude Code.
nanoTabPFN implemented in JAX
Rust: Usability for a Lifetime? - An Empirical Approach
The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.
Open Source Impact
Contributions to external projects
