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cs.LG2026
FM-fMRI: Event Conditioned Flow Matching for Rest-to-Task fMRI Time-Series Synthesis
Peiyu Duan, Jiyao Wang, Nicha C. Dvornek +4
Task-based fMRI provides a direct readout of task-evoked neural dynamics, but it is expensive and difficult to acquire at scale, motivating rest-to-task synthesis from widely avail…
cs.LG2026
Learning Robust and Task-Invariant Functional Representation from fMRI through Siamese Self-Supervised Learning
Jiyao Wang, Peiyu Duan, Nicha C. Dvornek +4
Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and the inherent subjectivity of…
cs.LG2024
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation
Tal Zeevi, Ravid Shwartz-Ziv, Yann LeCun +2
Accurate uncertainty estimation is crucial for deploying neural networks in risk-sensitive applications such as medical diagnosis. Monte Carlo Dropout is a widely used technique fo…