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Gabriel Schamberg
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2020 – today
- 2023
- [c7]Praveen Venkatesh
, Keerthana Gurushankar, Gabriel Schamberg:
Capturing and Interpreting Unique Information. ISIT 2023: 2631-2636 - [i9]Praveen Venkatesh, Keerthana Gurushankar, Gabriel Schamberg:
Capturing and Interpreting Unique Information. CoRR abs/2302.11873 (2023) - 2022
- [j4]Gabriel Schamberg, Marcus A. Badgeley, Benyamin Meschede-Krasa, Ohyoon Kwon
, Emery N. Brown:
Continuous action deep reinforcement learning for propofol dosing during general anesthesia. Artif. Intell. Medicine 123: 102227 (2022) - [c6]Praveen Venkatesh
, Gabriel Schamberg:
Partial Information Decomposition via Deficiency for Multivariate Gaussians. ISIT 2022: 2892-2897 - 2021
- [i8]Gabriel Schamberg, Praveen Venkatesh:
Partial Information Decomposition via Deficiency for Multivariate Gaussians. CoRR abs/2105.00769 (2021) - [i7]Blake Cole, Gabriel Schamberg:
Unscented Kalman Filter for Long-Distance Vessel Tracking in Geodetic Coordinates. CoRR abs/2111.13254 (2021) - 2020
- [j3]Gabriel Schamberg
, William Chapman
, Shang-Ping Xie
, Todd P. Coleman
:
Direct and Indirect Effects - An Information Theoretic Perspective. Entropy 22(8): 854 (2020) - [j2]Gabriel Schamberg
, Todd P. Coleman
:
Measuring Sample Path Causal Influences With Relative Entropy. IEEE Trans. Inf. Theory 66(5): 2777-2798 (2020) - [c5]Gabriel Schamberg, Sourish Chakravarty, Taylor E. Baum, Emery N. Brown:
Inferring neural dynamics during burst suppression using a neurophysiology-inspired switching state-space model. ACSSC 2020: 92-96 - [c4]Gabriel Schamberg, Marcus A. Badgeley, Emery N. Brown:
Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning. AIME 2020: 26-36 - [i6]Gabe Schamberg, Marcus A. Badgeley, Emery N. Brown:
Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning. CoRR abs/2008.12333 (2020)
2010 – 2019
- 2019
- [b1]Gabriel Schamberg:
Information Theoretic Measures and Estimators of Specific Causal Influences. University of California, San Diego, USA, 2019 - [c3]Gabriel Schamberg
, Todd P. Coleman:
On the Bias of Directed Information Estimators. ISIT 2019: 186-190 - [i5]Gabriel Schamberg, Todd P. Coleman:
On the Bias of Directed Information Estimators. CoRR abs/1902.00580 (2019) - [i4]Gabriel Schamberg, William Chapman, Shang-Ping Xie, Todd P. Coleman:
Direct and Indirect Effects - An Information Theoretic Perspective. CoRR abs/1912.10508 (2019) - 2018
- [j1]Gabriel Schamberg
, Demba E. Ba, Todd P. Coleman
:
A Modularized Efficient Framework for Non-Markov Time Series Estimation. IEEE Trans. Signal Process. 66(12): 3140-3154 (2018) - [c2]Gabriel Schamberg
, Todd P. Coleman:
A Sample Path Measure of Causal Influence. ISIT 2018: 2251-2255 - [i3]Gabriel Schamberg, Todd P. Coleman:
A Sample Path Measure of Causal Influence. CoRR abs/1805.03333 (2018) - [i2]Gabriel Schamberg, Todd P. Coleman:
Measuring Sample Path Causal Influences with Relative Entropy. CoRR abs/1810.05250 (2018) - 2017
- [i1]Gabriel Schamberg, Demba E. Ba, Todd P. Coleman:
A Modularized Efficient Framework for Non-Markov Time Series Estimation. CoRR abs/1706.04685 (2017) - 2016
- [c1]Gabriel Schamberg
, Demba E. Ba, Mark Wagner, Todd P. Coleman:
Efficient low-rank spectrotemporal decomposition using ADMM. SSP 2016: 1-5
Coauthor Index
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