4 papers
Self-supervised video pretraining yields robust and more human-aligned visual representations
Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira +1
Humans learn powerful representations of objects and scenes by observing how they evolve over time. Yet, outside of specific tasks that require explicit temporal understanding, sta…
Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding
Talfan Evans, Shreya Pathak, Hamza Merzic +3
Power-law scaling indicates that large-scale training with uniform sampling is prohibitively slow. Active learning methods aim to increase data efficiency by prioritizing learning…
Layerwise complexity-matched learning yields an improved model of cortical area V2
Nikhil Parthasarathy, Olivier J. Hénaff, Eero P. Simoncelli
Human ability to recognize complex visual patterns arises through transformations performed by successive areas in the ventral visual cortex. Deep neural networks trained end-to-en…
Data curation via joint example selection further accelerates multimodal learning
Talfan Evans, Nikhil Parthasarathy, Hamza Merzic +1
Data curation is an essential component of large-scale pretraining. In this work, we demonstrate that jointly selecting batches of data is more effective for learning than selectin…