-
Improving Transformation Invariance in Contrastive Representation Learning
We propose methods to strengthen the invariance properties of representa...
10/19/2020 ∙ by Adam Foster, et al. ∙
0
∙
share
read it
-
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
We introduce a fully stochastic gradient based approach to Bayesian opti...
11/01/2019 ∙ by Adam Foster, et al. ∙
23
∙
share
read it
-
Variational Estimators for Bayesian Optimal Experimental Design
Bayesian optimal experimental design (BOED) is a principled framework fo...
03/13/2019 ∙ by Adam Foster, et al. ∙
16
∙
share
read it
-
Variational Bayesian Optimal Experimental Design
Bayesian optimal experimental design (BOED) is a principled framework fo...
03/13/2019 ∙ by Adam Foster, et al. ∙
0
∙
share
read it
-
Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks
Empirical evidence suggests that heavy-tailed degree distributions occur...
07/09/2018 ∙ by Benjamin Bloem-Reddy, et al. ∙
4
∙
share
read it
