Gabriel Schamberg

According to our database, Gabriel Schamberg authored at least 14 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Dynamic Estimation of Cardiovascular State From Arterial Blood Pressure Recordings.

Taylor E. Baum, Elie M. Adam, Christian S. Guay, Gabriel Schamberg, Mohammadreza Kazemi, Thomas Heldt, Emery N. Brown

IEEE Trans. Biomed. Eng., November, 2024

2023

Capturing and Interpreting Unique Information.

Praveen Venkatesh, Keerthana Gurushankar, Gabriel Schamberg

Proceedings of the IEEE International Symposium on Information Theory, 2023

2022

Continuous action deep reinforcement learning for propofol dosing during general anesthesia.

Gabriel Schamberg, Marcus A. Badgeley, Benyamin Meschede-Krasa, Ohyoon Kwon, Emery N. Brown

Artif. Intell. Medicine, 2022

Partial Information Decomposition via Deficiency for Multivariate Gaussians.

Praveen Venkatesh, Gabriel Schamberg

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Unscented Kalman Filter for Long-Distance Vessel Tracking in Geodetic Coordinates.

Blake Cole, Gabriel Schamberg

CoRR, 2021

2020

Measuring Sample Path Causal Influences With Relative Entropy.

Gabriel Schamberg, Todd P. Coleman

IEEE Trans. Inf. Theory, 2020

Direct and Indirect Effects - An Information Theoretic Perspective.

Gabriel Schamberg, William Chapman, Shang-Ping Xie, Todd P. Coleman

Entropy, 2020

Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning.

Gabriel Schamberg, Marcus A. Badgeley, Emery N. Brown

Proceedings of the Artificial Intelligence in Medicine, 2020

Inferring neural dynamics during burst suppression using a neurophysiology-inspired switching state-space model.

Gabriel Schamberg, Sourish Chakravarty, Taylor E. Baum, Emery N. Brown

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Information Theoretic Measures and Estimators of Specific Causal Influences.

Gabriel Schamberg

PhD thesis, 2019

On the Bias of Directed Information Estimators.

Gabriel Schamberg, Todd P. Coleman

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

A Modularized Efficient Framework for Non-Markov Time Series Estimation.

Gabriel Schamberg, Demba E. Ba, Todd P. Coleman

IEEE Trans. Signal Process., 2018

A Sample Path Measure of Causal Influence.

Gabriel Schamberg, Todd P. Coleman

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2016

Efficient low-rank spectrotemporal decomposition using ADMM.

Gabriel Schamberg, Demba E. Ba, Mark Wagner, Todd P. Coleman

Proceedings of the IEEE Statistical Signal Processing Workshop, 2016