116 citations · 211 across the 4 of their papers we have counts for
5 papers
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders
Kevin Frans, L. B. Soros, Olaf Witkowski
This work presents CLIPDraw, an algorithm that synthesizes novel drawings based on natural language input. CLIPDraw does not require any training; rather a pre-trained CLIP languag…
Selecting for Selection: Learning To Balance Adaptive and Diversifying Pressures in Evolutionary Search
Kevin Frans, L. B. Soros, Olaf Witkowski
Inspired by natural evolution, evolutionary search algorithms have proven remarkably capable due to their dual abilities to radiantly explore through diverse populations and to con…
Population-Based Evolution Optimizes a Meta-Learning Objective
Kevin Frans, Olaf Witkowski
Meta-learning models, or models that learn to learn, have been a long-desired target for their ability to quickly solve new tasks. Traditional meta-learning methods can require exp…
Unsupervised Image to Sequence Translation with Canvas-Drawer Networks
Kevin Frans, Chin-Yi Cheng
Encoding images as a series of high-level constructs, such as brush strokes or discrete shapes, can often be key to both human and machine understanding. In many cases, however, da…
Meta Learning Shared Hierarchies
Kevin Frans, Jonathan Ho, Xi Chen +2
We develop a metalearning approach for learning hierarchically structured policies, improving sample efficiency on unseen tasks through the use of shared primitives---policies that…