kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning

arXiv:2512.21409 · cs.LG · Submitted 2025-12-24 · Read on arXiv

cs.LG

Submitted: 2025-12-24

Updated: 2026-01-08

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Infinitesimal Generator — 1× in this paper · explained in 2 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks