Software
| Author(s) or research group | Title | brief description of what the software does | language | URL for documentation / manual / tutorial | URL for code, if different / open source | URL of associated paper(s), if applicable | year of latest software release |
|---|---|---|---|---|---|---|---|
| Cécile Ané | PhyloNetworks.jl | Inference and manipulation of phylogenetic networks, and their use for trait evolution | Julia | https://juliaphylo.github.io/PhyloNetworks.jl/dev | https://github.com/juliaphylo/PhyloNetworks.jl | https://doi.org/10.1093/molbev/msx235 | 2025 |
| Vivak Patel, Daniel Adrian Maldonado | RandLinearAlgebra.jl | Deploy randomized linear solvers | Julia | https://numlinalg.github.io/RandLinearAlgebra.jl/dev | https://github.com/numlinalg/RandLinearAlgebra.jl | 2025 | |
| 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 | 2022 | |
| 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 | 2023 | ||
| 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 | 2023 | |
| 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 | 2023 | |
| 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 | 2023 | |
| Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett | Auto-differentiable Ensemble Kalman Filters (AD-EnKF) | Code for https://epubs.siam.org/doi/abs/10.1137/21M1434477 | Python | https://github.com/ymchen0/torchEnKF | https://epubs.siam.org/doi/abs/10.1137/21M1434477 | 2023 | |
| Elena Orlova, Haokun Liu, Raphael Rossellini, Benjamin Cash, Rebecca Willett | Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting | Code for https://arxiv.org/abs/2211.15856 | Python | https://github.com/elena-orlova/SSF-project | https://arxiv.org/abs/2211.15856 | 2023 | |
| Ruoxi Jiang, Rebecca Willett | Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification | Code for https://arxiv.org/abs/2211.01554 | Python | https://github.com/roxie62/Embed-and-Emulate | https://arxiv.org/abs/2211.01554 | 2023 | |
| Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak | Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization | Code for https://arxiv.org/abs/2305.16534 | Python | https://github.com/joeshenouda/vv-spaces-nn-width | https://arxiv.org/abs/2305.16534 | ||
| Karan Srivastava | Generating large isosceles-free lattice subsets with reinforcement learning | Code for training models and repository maintained for research | Python | https://github.com/ksrivastava1/isosceles_triangles_rl | |||
| Cécile Ané, Benjamin Teo, Paul Bastide | PhyloGaussianBeliefProp.jl | Analysis of Gaussian models on phylogenetic networks and admixture graphs using belief propagation | Julia | https://github.com/juliaphylo/PhyloGaussianBeliefProp.jl | https://arxiv.org/abs/2405.09327 | 2024 | |
| Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak | LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning | Code for https://openreview.net/forum?id=Y2QcZfwHE7 | Python | https://github.com/EfficientTraining/LabelBench | https://openreview.net/forum?id=Y2QcZfwHE7 | 2024 | |
| Jifan Zhang, Shuai Shao, Saurabh Verma, Robert Nowak | TAILOR | Code for: https://arxiv.org/abs/2302.07317 | Python | https://github.com/jifanz/TAILOR | https://arxiv.org/abs/2302.07317 | 2024 | |
| Brahma S. Pavse, Matthew Zurek, Yudong Chen, Qiaomin Xie, Josiah P. Hanna | STOP (STability and OPtimality) | Code for: https://openreview.net/pdf?id=64fdhmogiD | Python | https://github.com/Badger-RL/STOP | https://openreview.net/pdf?id=64fdhmogiD | 2024 | |
| Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, and Qiaomin Xie | Game Modification | Minimally modifying a Markov game to achieve any Nash Equilibrium and value. | Python | https://github.com/YoungWu559/game-modification | https://pages.cs.wisc.edu/~jerryzhu/pub/icml24.pdf | 2024 | |
| Jiaxin Hu and Miaoyan Wang | snQTL | Spectral Network Quantitative Trait Loci (snQTL) Analysis | R, C++ | https://cran.r-project.org/web/packages/snQTL/snQTL.pdf | https://doi.org/10.1371/journal.pcbi.1012953 | 2025 | |
| Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV, Sui Jiet Tay, Ramya Korlakai Vinayak, Frederic Sala | PabLO-SSL | Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL | Python | https://github.com/harit7/PabLO-SSL | https://openreview.net/pdf?id=w4c5bLkhsz | 2025 | |
| Cécile Ané and Paul Bastide | PhyloTraits.jl | analysis of trait evolution along a phylogeny, including phylogenetic networks | Julia | https://juliaphylo.github.io/PhyloTraits.jl/dev/ | https://github.com/JuliaPhylo/PhyloTraits.jl | https://doi.org/10.64898/2026.03.10.710880 | 2026 |
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