5 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.CV2022★ 5 cited
Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods
Skanda Koppula, Yazhe Li, Evan Shelhamer +5
Self-supervised methods have achieved remarkable success in transfer learning, often achieving the same or better accuracy than supervised pre-training. Most prior work has done so…
cs.CV2020★ 4 cited
Self-Supervised Learning of a Biologically-Inspired Visual Texture Model
Nikhil Parthasarathy, Eero P. Simoncelli
We develop a model for representing visual texture in a low-dimensional feature space, along with a novel self-supervised learning objective that is used to train it on an unlabele…
cs.LG2019
A Linear Systems Theory of Normalizing Flows
Reuben Feinman, Nikhil Parthasarathy
Normalizing Flows are a promising new class of algorithms for unsupervised learning based on maximum likelihood optimization with change of variables. They offer to learn a factori…