HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
C. Lagemann, S. Mokbel, M. Gondrum, M. Ruettgers, J. Callaham, L. Paehler, S. Ahnert, N. Zolman, K. Lagemann, N.A. Adams, M. Meinke, W. Schroeder, J.C. Loiseau, E. Lagemann, S.L. Brunton.
arXiv preprint, 2025.

HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
C. Lagemann, L. Paehler, J. Callaham, E. Lagemann, S. Mokbel, S. Ahnert, N.A. Adams, S.L. Brunton.
7th Annual Learning for Dynamics & Control Conference 2025 (L4DC).

ComPile: A Large IR Dataset from Production Sources
A. Grossman, L. Paehler, K. Parasyris, T. Ben-Nun, J. Hegna, W.S. Moses, J. Monsalve-Diaz, M. Trofin, J. Doerfert.
Journal of Data-centric Machine Learning Research, 2024.

Koopman-Assisted Reinforcement Learning
P. Rozwood, E.J. Mehrez, L. Paehler, W. Sun, S.L. Brunton.
AI4Science Workshop at the 37th Annual Conference on Neural Information Processing Systems (NeurIPS), 2023. Oral, Best Poster Award.

LLVM IR Dataset Utils
A. Grossman, L. Paehler, K. Parasyris, T. Ben-Nun, J. Hegna, W.S. Moses, J. Monsalve-Diaz, M. Trofin, J. Doerfert.
Zenodo, 2023.

TuringLang/Turing.jl: v0.29.2
K. Xu, H. Ge, C. Pfiffer, D. Widmann, M. Trapp, T. Erland Fjelde, Mathieue, W. Tebbutt, A. Scibor, K.Q. Zhuo, H. Mehr, E. Smith, P. Gabler, J. Rz, R. Huijzer, H. Wilde, A. Lui, P. Monticone, T. Roeschinger, azev77, K. Kim, A. Noack, D. Aluthge, F. Wantiez, H. Zhang, Jeremiah, J.D. Trattner, L. Paehler.
Zenodo, 2023.

SIAM Conference on Computational Science and Engineering Minitutorial: Integrating Scientific Simulations with Machine Learning Applications
S. Krishna-Narayanan, L. Paehler, J. Hueckelheim.
Zenodo, 2023.

Transparent Checkpointing for Automatic Differentiation of Program Loops through Expression Transformation
M. Schanen, S. Krishna-Narayanan, S. Williamson, V. Churavy, W.S. Moses, L. Paehler.
International Conference on Computational Science, 2023.

Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation
W.S. Moses, S. Krishna-Narayanan, L. Paehler, V. Churavy, M. Schanen, J. Hueckelheim, J. Doerfert, P. Hovland.
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'22). Nominated for best student-led paper & best paper awards, won best student-led paper award.

On the Relationship between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods
A. Toshev, L. Paehler, A. Panizza, N.A. Adams.
AI4Science Workshop at the International Conference on Machine Learning (ICML), 2022.

Reverse-Mode Automatic Differentiation and Optimization of GPU Kernels via Enzyme
W.S. Moses, V.Churavy, L. Paehler, J. Hueckelheim, S. Krishna-Narayanan, M. Schanen, J. Doerfert.
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'21). Nominated for best student-led paper award.

Sparse Identification of Truncation Errors
S. Thaler, L.Paehler, N.A. Adams.
Journal of Computational Physics, 2019.