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Found 4 papers, 1 papers with code
Test-Time Training for Generalization under Distribution Shifts
We introduce a general approach, called test-time training, for improving the performance of predictive models when training and test data come from different distributions.
The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement
In this paper, we propose the Hessian Penalty, a simple regularization term that encourages the Hessian of a generative model with respect to its input to be diagonal.
Morphology-Agnostic Visual Robotic Control
Existing approaches for visuomotor robotic control typically require characterizing the robot in advance by calibrating the camera or performing system identification.
A Computer Vision Pipeline for Automated Determination of Cardiac Structure and Function and Detection of Disease by Two-Dimensional Echocardiography
Automated cardiac image interpretation has the potential to transform clinical practice in multiple ways including enabling low-cost serial assessment of cardiac function in the primary care and rural setting.
