research
∙
07/20/2023
Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data
Recent advances in neuroscientific experimental techniques have enabled ...
share
research
∙
02/23/2023
Capturing and Interpreting Unique Information
Partial information decompositions (PIDs), which quantify information in...
research
∙
10/26/2022
Extracting Unique Information Through Markov Relations
We propose two new measures for extracting the unique information in X a...
research
∙
06/16/2022
Quantifying Feature Contributions to Overall Disparity Using Information Theory
When a machine-learning algorithm makes biased decisions, it can be help...
research
∙
11/30/2021
Fast and Real-time End to End Control in Autonomous Racing Cars Through Representation Learning
The challenges presented in an autonomous racing situation are distinct ...
research
∙
11/09/2021
Can Information Flows Suggest Targets for Interventions in Neural Circuits?
Motivated by neuroscientific and clinical applications, we empirically e...
research
∙
06/27/2021
Memory Guided Road Detection
In self driving car applications, there is a requirement to predict the ...
research
∙
05/03/2021
Partial Information Decomposition via Deficiency for Multivariate Gaussians
We consider the problem of decomposing the information content of three ...
research
∙
06/14/2020
Fairness Under Feature Exemptions: Counterfactual and Observational Measures
With the growing use of AI in highly consequential domains, the quantifi...
research
∙
02/06/2019
Information Flow in Computational Systems
We develop a theoretical framework for defining and identifying flows of...
research
∙
11/29/2018