546 citations · 1.4k across the 15 of their papers we have counts for
6 papers · 1 filter
Spectral Bias in Practice: The Role of Function Frequency in Generalization
Sara Fridovich-Keil, Raphael Gontijo-Lopes, Rebecca Roelofs
Despite their ability to represent highly expressive functions, deep learning models seem to find simple solutions that generalize surprisingly well. Spectral bias -- the tendency…
Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim +8
Large pre-trained models such as CLIP or ALIGN offer consistent accuracy across a range of data distributions when performing zero-shot inference (i.e., without fine-tuning on a sp…
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
Anders Andreassen, Yasaman Bahri, Behnam Neyshabur +1
Although machine learning models typically experience a drop in performance on out-of-distribution data, accuracies on in- versus out-of-distribution data are widely observed to fo…
Scene Transformer: A unified architecture for predicting multiple agent trajectories
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan +11
Predicting the motion of multiple agents is necessary for planning in dynamic environments. This task is challenging for autonomous driving since agents (e.g. vehicles and pedestri…
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
David Berthelot, Rebecca Roelofs, Kihyuk Sohn +2
We extend semi-supervised learning to the problem of domain adaptation to learn significantly higher-accuracy models that train on one data distribution and test on a different one…
Pseudo-labeling for Scalable 3D Object Detection
Benjamin Caine, Rebecca Roelofs, Vijay Vasudevan +4
To safely deploy autonomous vehicles, onboard perception systems must work reliably at high accuracy across a diverse set of environments and geographies. One of the most common te…