FlatClip: A Geometry-Aware Surface-Level Baseline for fMRI Representation Learning
cs.CE, cs.CV, q-bio.NC
Submitted: 2026-09-25
Updated: 2026-09-25
Terminology
Sources
- SLIM-Brain: A Data- and Training-Efficient Foundation Model for fMRI Data Analysis
- Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining
- BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics
- Scaling Vision Transformers for Functional MRI with Flat Maps
- DINOv2: Learning Robust Visual Features without Supervision
- SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
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