Cover Image

Hierarchical Inference and Closure Learning via Adaptive Surrogates for ODEs and PDEs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Pengyu, Vadeboncoeur, Arnaud, Glyn-Davies, Alex, Girolami, Mark
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Probabilistic Super-Resolution for High-Fidelity Physical System Simulations with Uncertainty Quantification
by: Zhang, Pengyu, et al.
Published: (2025)

A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
by: Glyn-Davies, Alex, et al.
Published: (2024)

Efficient Deconvolution in Populational Inverse Problems
by: Vadeboncoeur, Arnaud, et al.
Published: (2025)

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
by: Vadeboncoeur, Arnaud, et al.
Published: (2025)

Efficient Prior Calibration From Indirect Data
by: Akyildiz, O. Deniz, et al.
Published: (2024)

$Φ$-DVAE: Physics-Informed Dynamical Variational Autoencoders for Unstructured Data Assimilation
by: Glyn-Davies, Alex, et al.
Published: (2022)

Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
by: Grozavescu, Rares, et al.
Published: (2026)

Sumudu Neural Operator for ODEs and PDEs
by: Zelenskiy, Ben, et al.
Published: (2025)

Efficient Deconvolution in Populational Inverse Problems
by: Arnaud Vadeboncoeur, et al.
Published: (2026)

Towards Efficient and Stable Ocean State Forecasting: A Continuous-Time Koopman Approach
by: Grozavescu, Rares, et al.
Published: (2026)

Towards Foundation Inference Models that Learn ODEs In-Context
by: Mauel, Maximilian, et al.
Published: (2025)

Distributional Inverse Homogenization
by: Vadeboncoeur, Arnaud, et al.
Published: (2026)

Generating Origin-Destination Matrices in Neural Spatial Interaction Models
by: Zachos, Ioannis, et al.
Published: (2024)

Adaptive Feedforward Gradient Estimation in Neural ODEs
by: Dabounou, Jaouad
Published: (2024)

Adaptive tumor growth forecasting via neural & universal ODEs
by: Subramanian, Kavya, et al.
Published: (2025)

Statistical Finite Elements via Interacting Particle Langevin Dynamics
by: Glyn-Davies, Alex, et al.
Published: (2024)

Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models
by: Tang, Jiaqi, et al.
Published: (2025)

Learning to Discretize Denoising Diffusion ODEs
by: Tong, Vinh, et al.
Published: (2024)

Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary Domains
by: Wen, Shizheng, et al.
Published: (2025)

Towards Reliable Simulation-based Inference
by: Delaunoy, Arnaud
Published: (2026)

Gradient Scaling Effects in Adaptive Spectral PINNs for Stiff Nonlinear ODEs
by: Yepes, Isabela M., et al.
Published: (2026)

Learning via Surrogate PAC-Bayes
by: Picard-Weibel, Antoine, et al.
Published: (2024)

Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
by: Kim, Hojin, et al.
Published: (2025)

Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs
by: Menon, Sidharth S., et al.
Published: (2025)

Learning to Integrate Diffusion ODEs by Averaging the Derivatives
by: Liu, Wenze, et al.
Published: (2025)

AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Control
by: Yu, Shao-Yi, et al.
Published: (2025)

2DNMRGym: An Annotated Experimental Dataset for Atom-Level Molecular Representation Learning in 2D NMR via Surrogate Supervision
by: Li, Yunrui, et al.
Published: (2025)

Dynamics of Learning: Generative Schedules from Latent ODEs
by: Sampson, Matt L., et al.
Published: (2025)

Fast Inference via Hierarchical Speculative Decoding
by: Mohri, Clara, et al.
Published: (2025)

Riemannian Laplace Approximation with the Fisher Metric
by: Yu, Hanlin, et al.
Published: (2023)

Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
by: Reiser, Philipp, et al.
Published: (2023)

Surrogate Representation Inference for Text and Image Annotations
by: Nakamura, Kentaro
Published: (2025)

Switched Flow Matching: Eliminating Singularities via Switching ODEs
by: Zhu, Qunxi, et al.
Published: (2024)

Bayesian Gaussian Process ODEs via Double Normalizing Flows
by: Xu, Jian, et al.
Published: (2023)

Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
by: Ning, Alex, et al.
Published: (2025)

Targeted Separation and Convergence with Kernel Discrepancies
by: Barp, Alessandro, et al.
Published: (2022)

Warped geometric information on the optimisation of Euclidean functions
by: Hartmann, Marcelo, et al.
Published: (2023)

Low-Regret and Low-Complexity Learning for Hierarchical Inference
by: Chattopadhyay, Sameep, et al.
Published: (2025)

Scalable Inference-Time Annealing with Surrogate Likelihood Estimators
by: Peñaherrera, Daniel, et al.
Published: (2026)

From Complex Dynamics to DynFormer: Rethinking Transformers for PDEs
by: Lai, Pengyu, et al.
Published: (2026)