Journal Articles
- M. Burkhart & G. Ruiz. Neuroevolutionary representations for learning heterogeneous treatment effects. Journal of Computational Science 71 (2023) [pdf]
- M. Burkhart. Discriminative Bayesian filtering lends momentum to the stochastic Newton method for minimizing log-convex functions. Optimization Letters 17 (2023) [pdf] [MR4557438]
- M. Burkhart. Conjugacy conditions for supersoluble complements of an abelian base and a fixed point result for non-coprime actions. Proceedings of the Edinburgh Mathematical Society 65 (2022) [pdf] [MR4542651]
- M. Burkhart, D. Brandman, B. Franco, L. Hochberg, & M. Harrison. The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models. Neural Computation 32 (2020) [pdf] [MR4101168]
- D. Brandman, M. Burkhart, J. Kelemen, B. Franco, M. Harrison, & L. Hochberg. Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression. Neural Computation 30 (2018) [pdf] [MR3873814]
- D. Brandman, T. Hosman, J. Saab, M. Burkhart, B. Shanahan, J. Ciancibello, …, M. Harrison, J. Simeral, & L. Hochberg. Rapid calibration of an intracortical brain computer interface for people with tetraplegia. Journal of Neural Engineering 15 (2018)
- M. Burkhart, Y. Heo, & V. Zavala. Measurement and verification of building systems under uncertain data: A Gaussian process modeling approach. Energy and Buildings 75 (2014)