Michael C. Burkhart

Orcid: 0000-0002-2772-5840

According to our database1, Michael C. Burkhart authored at least 11 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2023
Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functions.
Optim. Lett., April, 2023

Neuroevolutionary representations for learning heterogeneous treatment effects.
J. Comput. Sci., 2023

2022
Neuroevolutionary Feature Representations for Causal Inference.
Proceedings of the Computational Science - ICCS 2022, 2022

2021
Discriminative Bayesian Filtering for the Semi-supervised Augmentation of Sequential Observation Data.
Proceedings of the Computational Science - ICCS 2021, 2021

2020
The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models.
Neural Comput., 2020

Deep Low-Density Separation for Semi-supervised Classification.
Proceedings of the Computational Science - ICCS 2020, 2020

2019
A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding. (Une approche discriminante du filtrage bayésien avec des applications au décodage neuronal humain).
PhD thesis, 2019

Adaptive Objective Functions and Distance Metrics for Recommendation Systems.
Proceedings of the Computational Science - ICCS 2019, 2019

Determining Adaptive Loss Functions and Algorithms for Predictive Models.
Proceedings of the Computational Science - ICCS 2019, 2019

2018
Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression.
Neural Comput., 2018

A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding.
CoRR, 2018


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