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Author(s)	Title	Description	Language	Documentation	Code	Papers
Cécile Ané	PhyloNetworks	Inference and manipulation of phylogenetic networks, and their use for trait evolution	Julia	https://crsl4.github.io/PhyloNetworks.jl/dev/	https://github.com/crsl4/PhyloNetworks.jl	https://doi.org/10.1093/molbev/msx235
Cécile Ané	PhyloPlots	phylogenetic network visualization		https://cecileane.github.io/PhyloPlots.jl/dev
Cécile Ané	QuartetNetworkGoodnessFit	phylogenetic networks analyses using four-taxon subsets		https://cecileane.github.io/QuartetNetworkGoodnessFit.jl/dev/
Cécile Ané	PhyloCoalSimulations	simulate phylogenies under the coalescent		https://cecileane.github.io/PhyloCoalSimulations.jl/dev/
Vivak Patel, Daniel Adrian Maldonado	RLinearAlgebra.jl	Deploy randomized linear solvers	Julia	https://numlinalg.github.io/RLinearAlgebra.jl/dev/	https://github.com/numlinalg/RLinearAlgebra.jl
Sameer Deshpande	flexBART	A faster and more flexible implementation of Bayesian Additive Regression Trees	R, C++	https://github.com/skdeshpande91/flexBART		https://arxiv.org/abs/2211.04459
Owen Melia, Eric Jonas, Rebecca Willett	Rotation Invariant Random Features	Code for "Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds"	Python	https://github.com/meliao/rotation-invariant-random-features
Suzanna Parkinson, Greg Ongie, Rebecca Willett	Linear layers in neural networks	Code for https://arxiv.org/abs/2305.15598	Python	https://github.com/suzannastep/linearlayers		https://arxiv.org/abs/2305.15598
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett	Deep Stochastic Mechanics	Code for https://arxiv.org/abs/2305.19685	Python	https://github.com/elena-orlova/deep-stochastic-mechanics		https://arxiv.org/abs/2305.19685
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett	Reduced-Order Autodifferentiable Ensemble Kalman Filters (ROAD-EnKF)	Code for https://arxiv.org/abs/2301.11961	Python	https://github.com/ymchen0/ROAD-EnKF		https://arxiv.org/abs/2301.11961

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Books

Ellenberg, Jordan, Shape: The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else, Penguin Books, 2022. https://www.penguinrandomhouse.com/books/612131/shape-by-jordan-ellenberg/

Wright, Stephen J., and Benjamin Recht, Optimization for Data Analysis, Cambridge University Press, 2022. https://doi.org/10.1017/9781009004282

Diakonikolas, Ilias, and Daniel M. Kane, Algorithmic High-Dimensional Robust Statistics, Cambridge University Press, 2023. https://doi.org/10.1017/9781108943161

Nan Chen, Stochastic Methods for Modeling and Predicting Complex Dynamical Systems, Springer Cham, 2024. https://doi.org/10.1007/978-3-031-22249-8

Roch, Sebastien, Modern Discrete Probability: An Essential Toolkit, Cambridge University Press, 2024. https://doi.org/10.1017/9781009305129

Educational Materials & Tools

Online textbook on “Mathematical Methods in Data Science (with Python)” by Sebastien Roch. https://mmids-textbook.github.io/

Online tutorial on “Comparative methods on reticulate phylogenies”. https://cecileane.github.io/networkPCM-workshop/

Online textbook on “Causal Inference” by Amy Cochran: https://amy-cochran.gitbook.io/causal-inference

Lecture notes for a year-long course on the “Mathematics of Data Science” by Dmitriy Drusvyatskiy: https://sites.math.washington.edu/~ddrusv/crs/Math_581_2023/MATH581.html

Lecture notes and video lectures for a course on the “Mathematical Foundations of Machine Learning” by Rebecca Willett: https://willett.psd.uchicago.edu/teaching/mathematical-foundations-of-machine-learning-fall-2021/

Autograder: a server to automatically grading coding assignments. https://github.com/edulinq/autograder-server

Quiz Generator: allows a general format for quiz banks, that then can be uploaded in a variety of forms (gradescope, Canvas, pdf, html, qti, etc.); support for latex, wide variety of question types; and allows support for collaboration by using standard tools like git for managing questions. https://github.com/edulinq/quizgen

Canvas Tools: a suite of tools and Python interface for Instructure’s Canvas LMS. https://github.com/edulinq/py-canvas