3 papers
cs.CV2025
From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations
Anthony Bisulco, Rahul Ramesh, Randall Balestriero +1
Masked Autoencoders (MAEs) have emerged as a powerful pretraining technique for vision foundation models. Despite their effectiveness, they require extensive hyperparameter tuning…
cs.CV2025
Many Perception Tasks are Highly Redundant Functions of their Input Data
Rahul Ramesh, Anthony Bisulco, Ronald W. DiTullio +4
We show that many perception tasks, from visual recognition, semantic segmentation, optical flow, depth estimation to vocalization discrimination, are highly redundant functions of…
stat.ML2025
Prospective Learning: Learning for a Dynamic Future
Ashwin De Silva, Rahul Ramesh, Rubing Yang +3
In real-world applications, the distribution of the data, and our goals, evolve over time. The prevailing theoretical framework for studying machine learning, namely probably appro…