Residual-augmented flow matching operators for probabilistic partial differential equations
stat.CO, cs.LG, stat.ML
Submitted: 2025-12-14
Updated: 2026-09-05
Code: https://github.com/sahilbhola14/floral
Terminology
Sources
- Stochastic Flow Matching for Resolving Small-Scale Physics
- CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
- Diffusion Generative Models in Infinite Dimensions
- Functional Flow Matching
- A Library for Learning Neural Operators
- Fourier Neural Operator for Parametric Partial Differential Equations
- Neural Operator: Graph Kernel Network for Partial Differential Equations
- Flow Matching for Generative Modeling
- Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs
- E-PINNs: Epistemic Physics-Informed Neural Networks
- Infinite-Dimensional Diffusion Models
- Generative Adversarial Neural Operators
- Stochastic Process Learning via Operator Flow Matching
- Denoising Diffusion Implicit Models
- Multi-fidelity wavelet neural operator with application to uncertainty quantification
- Improving and generalizing flow-based generative models with minibatch optimal transport
- A Denoising Diffusion Model for Fluid Field Prediction
- Guided Diffusion Sampling on Function Spaces with Applications to PDEs
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