research
∙
05/12/2023
Designing Optimal Behavioral Experiments Using Machine Learning
Computational models are powerful tools for understanding human cognitio...
share
research
∙
08/17/2022
Domain Knowledge in A*-Based Causal Discovery
Causal discovery has become a vital tool for scientists and practitioner...
research
∙
04/29/2022
Statistical applications of contrastive learning
The likelihood function plays a crucial role in statistical inference an...
research
∙
11/03/2021
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods
We introduce implicit Deep Adaptive Design (iDAD), a new method for perf...
research
∙
10/29/2021
Bayesian Optimal Experimental Design for Simulator Models of Cognition
Bayesian optimal experimental design (BOED) is a methodology to identify...
research
∙
05/10/2021
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds
We introduce a framework for Bayesian experimental design (BED) with imp...
research
∙
03/20/2020
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information
Bayesian experimental design (BED) is a framework that uses statistical ...
research
∙
02/19/2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
Implicit stochastic models, where the data-generation distribution is in...
research
∙
10/23/2018