Publications
Below is a list of my publications: click through the linked title for more details.
Submitted
C.R. Wentland, M. Weylandt, L.P. Swiler, T.S. Ehrmann, and D.Bull “Conditional multi-step attribution for climate forcings” 2024.
J.J. Nichol, M. Weylandt, G.M. Fricke, M. Moses, D. Bull, and L.P. Swiler. “Causal Spatiotemporal Stencil Learning: Local Causal Dynamics in Complex Systems.” 2024.
R. B. Lehoucq, M. Weylandt, and J. W. Berry. “Optimal accuracy for linear sets of equations with the graph Laplacian”. 2024.
C. O. Little†, M. Weylandt† and G. I. Allen. “To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier”. 2022.
M. Weylandt and G. Michailidis. “Multivariate Analysis for Multiple Network Data via Semi-Symmetric Tensor PCA”. 2022.
M. Weylandt and G. I. Allen. “Debiasing Projections for Fair Principal Components Analysis”. 2021.
M. Navarro, G. I. Allen, and M. Weylandt. “Network Clustering for Latent State and Changepoint Detection”. 2021.
M. Weylandt, Y. Han, and K. B. Ensor. “Multivariate Modeling of Natural Gas Spot Trading Hubs Incorporating Futures Market Realized Volatility”. 2019.
Winner of the ASA Section on Business and Economic Statistics (B&E) 2020 Student Paper Competition
A.P. Drager, M. Weylandt, G. Chuyong, D. Kenfack, D.W. Thomas, and A.E. Dunham. “Ecological correlates of reproductive status in a guild of Afrotropical understory trees.” 2019.
Published
M. Weylandt and L. P. Swiler. “Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints.” Journal of Climate 37(5), pp.1723-1735. 2024.
M. Weylandt, G. Michailidis, and T. M. Roddenberry. “Sparse Partial Least Squares for Coarse Noisy Graph Alignment.” SSP 2021: Proceedings of the 2021 IEEE Statistical Signal Processing Workshop 2021, pp.561-565. 2021.
M. Weylandt, T.M. Roddenberry, and G. I. Allen. “Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering.” DSLW 2021: Proceedings of the IEEE Data Science and Learning Workshop 2021. pp.1-8. 2021.
M. Weylandt and G. Michailidis. “Automatic Registration and Clustering of Time Series.” ICASSP 2021: Proceedings of the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.5609-5613. 2021.
J.S. Morris, M.M. Hassan, Y.E. Zohner, Z. Wang, L. Xiao, A. Rashid, A. Haque, R. Abdel-Wahad, Y.A. Mohamed, K.L. Ballard, R.A. Wolff, B. George, L. Li, G. I. Allen, M. Weylandt, D. Li, W. Wang, K. Raghav, J. Yao, H.M. Amin, and A.O. Kaseb. “HepatoScore‐14: Measures of biological heterogeneity significantly improve prediction of hepatocellular carcinoma risk.” Hepatology 73(6), pp. 2278-2292. 2021.
M. Weylandt. “Multi-Rank Sparse and Functional PCA: Manifold Optimization and Iterative Deflation Techniques.” CAMSAP 2019: Proceedings of the IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp.500-504. 2019.
M. Weylandt, J. Nagorski, and G. I. Allen. “Interactive Visualizations and Fast Computation for Convex Clustering via Algorithmic Regularization.” Journal of Computational and Graphical Statistics 29(1), pp. 87-96. 2020.
Winner of the ASA Section on Statistical Learning and Data Science (SLDS) 2019 Student Paper Competition
M. Weylandt. “Splitting Methods for Convex Bi-Clustering and Co-Clustering.” DSW 2019: Proceedings of the IEEE Data Science Workshop 2019, pp.237-244. 2019.
G. I. Allen and M. Weylandt. “Sparse and Functional Principal Components Analysis.” DSW 2019: Proceedings of the IEEE Data Science Workshop 2019, pp.11-16. 2019.
Other Professional Writing
M. Weylandt. “Computational and Statistical Methodology for Highly-Structured Data.” Ph.D. Thesis, Rice University. 2020.
L. Damiano, B. Peterson, and M. Weylandt. “A Tutorial on Hidden Markov Models using Stan.” StanCon 2018.
A BibTeX file for these publications can be found here.