StableTTA improves ImageNet-1K accuracy across 71 vision models by stabilizing logit aggregation under coherent-batch inference and enabling efficient single-forward-pass adaptation.
The elements of statistical learning: data mining, inference, and prediction
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Pretrained scalp-EEG foundation models can be transferred to ECoG via adapters and fine-tuning to match or exceed subject-specific baselines on regression tasks while requiring far less per-patient data.
DynoSys offers a unified dynamic systems model integrating genetic, environmental, and neurobiological signals to analyze longitudinal behavioral phenotypes in adolescents via harmonized representations and survival or state-space modeling.
citing papers explorer
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StableTTA: Improving Vision Model Performance by Training-free Test-Time Adaptation Methods
StableTTA improves ImageNet-1K accuracy across 71 vision models by stabilizing logit aggregation under coherent-batch inference and enabling efficient single-forward-pass adaptation.
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CORTEG: Foundation Models Enable Cross-Modality Representation Transfer from Scalp to Intracranial Brain Recordings
Pretrained scalp-EEG foundation models can be transferred to ECoG via adapters and fine-tuning to match or exceed subject-specific baselines on regression tasks while requiring far less per-patient data.
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DynoSys: A Dynamic Systems Framework for Multimodal Integration of Genetic, Environmental, and Neurobiological Signals
DynoSys offers a unified dynamic systems model integrating genetic, environmental, and neurobiological signals to analyze longitudinal behavioral phenotypes in adolescents via harmonized representations and survival or state-space modeling.