mlsanityData to 7 Oct 2026

Optimistix: modular optimisation in JAX and Equinox

arXiv 2402.09983 ↗First posted 15 Feb 2024math.OC cs.MScited by 17

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Abstract (arXiv)

We introduce Optimistix: a nonlinear optimisation library built in JAX and Equinox. Optimistix introduces a novel, modular approach for its minimisers and least-squares solvers. This modularity relies on new practical abstractions for optimisation which we call search and descent, and which generalise classical notions of line search, trust-region, and learning-rate algorithms. It provides high-level APIs and solvers for minimisation, nonlinear least-squares, root-finding, and fixed-point iteration. Optimistix is available at https://github.com/patrick-kidger/optimistix.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Feb 2024.

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Citing papers per year: 2025: 7; 2026: 10.

17 papers.

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  1. 2025Optimizing the Optimizer for Physics-Informed Neural Networks and Kolmogorov-Arnold Networkscited by 41
  2. 2025Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacologycited by 10
  3. 2026torch-sla: Differentiable Sparse Linear Algebra with Adjoint Solvers and Sparse Tensor Parallelism for PyTorchcited by 3
  4. 2026SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradientscited by 2
  5. 2026Self-Scaled Broyden Family of Quasi-Newton Methods in JAXcited by 2
  6. 2026Tackling Failure Modes of PINNs and PIKANs Using Conflict-Free Gradientscited by 2
  7. 2025Accelerating Natural Gradient Descent for PINNs with Randomized Numerical Linear Algebracited by 1
  8. 2025Towards real-time surrogate-free Bayesian inversion for neutron reflectometrycited by 0
  9. 2025Automated design of compound lenses with discrete-continuous optimizationcited by 0
  10. 2025Meshless solutions of PDE inverse problems on irregular geometriescited by 0
  11. 2025Case study of a differentiable heterogeneous multiphysics solver for a nuclear fusion applicationcited by 0
  12. 2026Second-Order, First-Class: A Composable Stack for Curvature-Aware Trainingcited by 0
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  2. 2026RAM: Reachability Across Morphologiescited by 0
  3. 2026SoRoMoX: Fast, Differentiable, and Parallelizable Soft Robot Modelscited by 0
  4. 2026GRADSOLVE: fast exact gradients for ODE ensembles on GPUscited by 0
  5. 2026Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Controlcited by 0