165 citations · 193 across the 4 of their papers we have counts for
4 papers
Dataset Factory: A Toolchain For Generative Computer Vision Datasets
Daniel Kharitonov, Ryan Turner
Generative AI workflows heavily rely on data-centric tasks - such as filtering samples by annotation fields, vector distances, or scores produced by custom classifiers. At the same…
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Ryan Turner, David Eriksson, Michael McCourt +4
This paper presents the results and insights from the black-box optimization (BBO) challenge at NeurIPS 2020 which ran from July-October, 2020. The challenge emphasized the importa…
Bayesian Hypernetworks
David Krueger, Chin-Wei Huang, Riashat Islam +3
We study Bayesian hypernetworks: a framework for approximate Bayesian inference in neural networks. A Bayesian hypernetwork $\h$ is a neural network which learns to transform a sim…
A Model Explanation System: Latest Updates and Extensions
Ryan Turner
We propose a general model explanation system (MES) for "explaining" the output of black box classifiers. This paper describes extensions to Turner (2015), which is referred to fre…