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Connor Lane

3 accepted papers

2026

Scaling Vision Transformers for Functional MRI with Flat Maps

ICML 2026poster

We propose a simple strategy for training a foundation model on functional MRI (fMRI) data: we adapt the standard Vision Transformer to fMRI by first converting each 3D fMRI volume to a 2D map using a standard cortical flat map projection. We train spatiotemporal masked autoencoders (MAE) on 2.3K ho…

Cited by 2SourceScholar
2018

Dropout as a Low-Rank Regularizer for Matrix Factorization

AISTATS 2018poster

Regularization for matrix factorization (MF) and approximation problems has been carried out in many different ways. Due to its popularity in deep learning, dropout has been applied also for this class of problems. Despite its solid empirical performance, the theoretical properties of dropout as a r…

Cited by 0SourcePDFScholar