Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:18:54.450114Z
Paper Citation Record · LEDGER
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates
As of 16 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2608.11435.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
61 of 61 outbound references displayed
- verified exact1
- verified fuzzy47
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2ffdde12-67d8-4eb2-b734-c9cfbdce5af3 · outbound
This paper cites A physics-informed meta-learning frame- work for the continuous solution of parametric pdes on arbitrary geometries,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A physics-informed meta-learning frame- work for the continuous solution of parametric pdes on arbitrary geometries,
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.010742Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5f24978-4e32-4396-8801-2a1632f5fa62 · outbound
This paper cites Parametric model order reduction for a wildland fire model via the shifted pod-based deep learning method,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Parametric model order reduction for a wildland fire model via the shifted pod-based deep learning method,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.919402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 15c4aefe-60af-4bbb-a4c9-3f0d7c02d89b · outbound
This paper cites A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized pdes,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized pdes,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.892394Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation de7db8e8-78de-49e0-9ba5-ed6552db7bb6 · outbound
This paper cites Reduced order modeling conditioned on monitored features for response and error bounds estimation in engineered systems,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Reduced order modeling conditioned on monitored features for response and error bounds estimation in engineered systems,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.874941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0a4f7a42-875a-4426-9f97-a36627f8b71e · outbound
This paper cites an unresolved cited work.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Unresolved cited work
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.049239Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7905b227-5d67-4d4b-98be-f6b1fcdfa321 · outbound
This paper cites an unresolved cited work.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:55.845931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e50b17a5-2638-411b-8177-d5a9408856a4 · outbound
This paper cites Parameter identification of fluid field based on cfd reduced-order model and 3d-var data assimilation,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Parameter identification of fluid field based on cfd reduced-order model and 3d-var data assimilation,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.823441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 46272a86-c72a-4793-9d5e-f87436e7cd73 · outbound
This paper cites Dynamic mode decomposition: Theory and applications,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Dynamic mode decomposition: Theory and applications,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.799579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 80678a23-4b69-4da5-acf3-0464a321b7a8 · outbound
This paper cites Ahybriddataassimilationanddynamicmodedecomposition approach for xenon dynamic prediction of nuclear reactor cores,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Ahybriddataassimilationanddynamicmodedecomposition approach for xenon dynamic prediction of nuclear reactor cores,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.783149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1bb06ef7-9cd1-431a-b7e8-74ef96cbb757 · outbound
This paper cites A kernel ridge regression combining nonlinear roms for accurate flow-field reconstruction with discontinuities,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A kernel ridge regression combining nonlinear roms for accurate flow-field reconstruction with discontinuities,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.766307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 025b573c-8db5-4664-a0b5-5092e6055718 · outbound
This paper cites Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.749998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation add600b4-7438-4c88-bf01-8cc969ad07bc · outbound
This paper cites A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.101683Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 912f29db-4504-496f-b10f-77410b5d7f26 · outbound
This paper cites A graph convolutional autoencoder approach to model order reduction for parametrized pdes,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A graph convolutional autoencoder approach to model order reduction for parametrized pdes,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.728676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6203bc1b-9fbc-4510-8507-a9354e1e72c9 · outbound
This paper cites Handling geometrical variability in nonlinear re- duced order modeling through continuous geometry-aware dl-roms,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Handling geometrical variability in nonlinear re- duced order modeling through continuous geometry-aware dl-roms,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.711575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dd645f8d-9fd2-4b40-8044-c6c097382e58 · outbound
This paper cites Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.683793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 57d87591-ba51-4941-a0c9-e88de4c2d084 · outbound
This paper cites Graspingextremeaerodynamicsonalow-dimensionalmanifold,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Graspingextremeaerodynamicsonalow-dimensionalmanifold,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.659436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 560fc76d-2465-4611-8a10-130a182dc8e6 · outbound
This paper cites Learning physics constrained dynamics using autoencoders,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Learning physics constrained dynamics using autoencoders,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.641717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ae9037b9-ef61-44f9-8f75-b5b614600c00 · outbound
This paper cites Observable-augmented manifold learning for multi-source tur- bulent flow data,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Observable-augmented manifold learning for multi-source tur- bulent flow data,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.622582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e552ad9f-779a-4a82-addf-f095017334cc · outbound
This paper cites Yuki algorithm and pod-rbf for elastostatic and dynamic crack identification,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Yuki algorithm and pod-rbf for elastostatic and dynamic crack identification,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.602620Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4e174f98-7d8d-4548-a838-130a5d5ed640 · outbound
This paper cites Deep neural network and yuki algorithm for inner damage characterization based on elastic boundary displacement,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Deep neural network and yuki algorithm for inner damage characterization based on elastic boundary displacement,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.581872Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e440ab17-e340-42e8-9d45-97e5c99ff6ee · outbound
This paper cites Machine learning with data assimilation and uncertainty quantification for dynamical systems: A review,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Machine learning with data assimilation and uncertainty quantification for dynamical systems: A review,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.562696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 488c9572-18a8-4995-a72a-5078e5e514e7 · outbound
This paper cites Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.534691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2266267c-e71b-49bc-ab15-c48fc1f68f38 · outbound
This paper cites an unresolved cited work.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:55.511124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ac005562-1559-4f19-8189-3bbc408b34d1 · outbound
This paper cites Data assimilation in the geosciences: An overview of methods, issues, and perspectives,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Data assimilation in the geosciences: An overview of methods, issues, and perspectives,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.492651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 8ac46493-f3a7-41a7-af50-68ad2f8bc313 · outbound
This paper cites The advantages of data assimi- lation in parametric space rather than classic grid space,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates The advantages of data assimi- lation in parametric space rather than classic grid space,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.470612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b3d3a580-a391-4276-9dbc-aa7334b0839c · outbound
This paper cites Enkf data-driven reduced order assimilation system,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Enkf data-driven reduced order assimilation system,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.433853Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f90a3fb0-0aac-4d41-8d30-ae237dd86dd6 · outbound
This paper cites Generalised latent assimilation in heterogeneous reduced spaces with machine learning surrogate models,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Generalised latent assimilation in heterogeneous reduced spaces with machine learning surrogate models,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.407548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 02fbee54-4930-4c59-9235-6a2282a45f9a · outbound
This paper cites Multi-domain encoder–decoder neural networks for latent data assimilation in dynamical systems,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Multi-domain encoder–decoder neural networks for latent data assimilation in dynamical systems,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.392894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4f268502-086b-4107-b536-f8a738e9f0d1 · outbound
This paper cites Application and comparison of several adaptive sampling algorithms in reduced order modeling,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Application and comparison of several adaptive sampling algorithms in reduced order modeling,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.374976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a45bebbe-dc00-4e39-bb48-955f55bd3aba · outbound
This paper cites Surrogate-based ensemble data assimilation forreducinguncertaintyinlarge-eddysimulationofmicroscalepollutantdispersion,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Surrogate-based ensemble data assimilation forreducinguncertaintyinlarge-eddysimulationofmicroscalepollutantdispersion,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.358903Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1ba7760f-56f6-4546-b841-94e6e22dcbc4 · outbound
This paper cites Torchda: A python package for performing data assimila- tion with deep learning forward and transformation functions,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Torchda: A python package for performing data assimila- tion with deep learning forward and transformation functions,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.339710Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 8a604fe4-0d55-44cb-ab3a-86c37dee4f2d · outbound
This paper cites CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.251075Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72b397ef-f600-41fc-886c-73fe2fbb03e3 · outbound
This paper cites Surrogate-based bayesian inverse modeling of the hydrological system: An adaptive approach considering surrogate approximation error,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Surrogate-based bayesian inverse modeling of the hydrological system: An adaptive approach considering surrogate approximation error,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.320521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 75e12864-a230-4197-afcc-356e46c4154a · outbound
This paper cites Uncertainty quantification and propagation in surrogate-based bayesian inference,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Uncertainty quantification and propagation in surrogate-based bayesian inference,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.301677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 12d7865b-54b2-46e9-8989-d8d472ed1dd3 · outbound
This paper cites Parametric probabilistic manifold decomposition for nonlinear model reduction,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Parametric probabilistic manifold decomposition for nonlinear model reduction,
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.283918Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47ea1207-7f69-4d7e-961c-48e717e28c67 · outbound
This paper cites Bayesian gaussian process latent variable model,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Bayesian gaussian process latent variable model,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.282140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5bddbb9f-e083-4728-8611-9d9b39f5e9c7 · outbound
This paper cites Mechanics-informed autoencoder enables auto- mated detection and localization of unforeseen structural damage,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Mechanics-informed autoencoder enables auto- mated detection and localization of unforeseen structural damage,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.262896Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f8baacf1-d49e-4fc7-84d7-f37557b329fa · outbound
This paper cites Physics-informed quantum neural network for solving forward and inverse problems of partial differential equations,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Physics-informed quantum neural network for solving forward and inverse problems of partial differential equations,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.248147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b6e7e945-f74c-4e73-bd9c-595faae6a2c3 · outbound
This paper cites Quantum machine learning for efficient reduced order mod- elling of turbulent flows,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Quantum machine learning for efficient reduced order mod- elling of turbulent flows,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.224779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 795c11e4-5cc0-42d7-81cc-7d212a3c9907 · outbound
This paper cites Qcpinn: Quantum-classical physics-informed neural networks for solving pdes,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Qcpinn: Quantum-classical physics-informed neural networks for solving pdes,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.200748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e3ed6aa9-67be-46b2-8549-b608d4583d9a · outbound
This paper cites Taflove,Computational electrodynamics the finite-difference time-domain method.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Taflove,Computational electrodynamics the finite-difference time-domain method
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.179003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dd7427ad-ba19-4a81-a246-4241ba421aa7 · outbound
This paper cites an unresolved cited work.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:55.163729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation acca1645-74d2-4889-848b-d4d35b803165 · outbound
This paper cites an unresolved cited work.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:55.145411Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2cd3be31-a0a2-4282-b14c-ccfddf81f0bc · outbound
This paper cites Ern and J.-L.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Ern and J.-L
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.125526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 89d4e72d-ea46-4075-8882-27361b430971 · outbound
This paper cites A spectral element method for the navier–stokes equations with improved accuracy,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A spectral element method for the navier–stokes equations with improved accuracy,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.095927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2b6a4306-aa47-4408-8be9-ab62b7084b3d · outbound
This paper cites State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.068893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b69215fa-b2d0-4407-8ec5-35459cdfad50 · outbound
This paper cites Generative learning of the solution of parametric partial differential equations using guided diffusion models and virtual obser- vations,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Generative learning of the solution of parametric partial differential equations using guided diffusion models and virtual obser- vations,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.051581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a8e21e49-8fb6-4873-8c97-f13ce7c647c4 · outbound
This paper cites Gaussian process regression+ deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Gaussian process regression+ deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.034605Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 71a04f3e-2079-42ad-99ef-2b66c889aec9 · outbound
This paper cites Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.376964Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5098e3ec-e2c3-415b-81be-2f2ec0d91652 · outbound
This paper cites A new approach to linear filtering and prediction problems,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A new approach to linear filtering and prediction problems,
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.382745Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6bc7cf7-c0d2-40a1-a129-da116f0db351 · outbound
This paper cites Efficientdataassimilationforspatiotemporal chaos: A local ensemble transform kalman filter,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Efficientdataassimilationforspatiotemporal chaos: A local ensemble transform kalman filter,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:55.006592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a5021252-aaa5-4e73-a3b2-f61bfd25bb58 · outbound
This paper cites 3d-var data assimilation using a variational autoencoder,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates 3d-var data assimilation using a variational autoencoder,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.978695Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d7691371-830c-4b69-8b49-22b3534bc33a · outbound
This paper cites Efficient deep data assimilation with sparse observations and time-varying sensors,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Efficient deep data assimilation with sparse observations and time-varying sensors,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.957105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0f9762de-2080-427f-adc8-ac0ad3b4048d · outbound
This paper cites Parameter estimation for land-surface mod- els using machine learning libraries,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Parameter estimation for land-surface mod- els using machine learning libraries,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.935231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5da5bd9c-8530-4f00-ba85-d13bbd37fdeb · outbound
This paper cites Parameter flexible wildfire prediction using ma- chine learning techniques: Forward and inverse modelling,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Parameter flexible wildfire prediction using ma- chine learning techniques: Forward and inverse modelling,
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.914597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 0c536c0e-1e0c-4644-aac9-7621c1b81edb · outbound
This paper cites Residual Data-Driven Variational Multiscale Reduced Order Models for Parameter Dependent Problems.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Residual Data-Driven Variational Multiscale Reduced Order Models for Parameter Dependent Problems
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:54.419217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0bbdc54-a34d-4aa6-b4af-1e57ff10020b · outbound
This paper cites Estimating Varying Parameters in Dynamical Systems: A Modular Framework Using Switch Detection, Optimization, and Sparse Regression.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Estimating Varying Parameters in Dynamical Systems: A Modular Framework Using Switch Detection, Optimization, and Sparse Regression
Reference 57
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:18:54.590634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 76d48009-31ea-4e30-b5c0-736ce09b046e · outbound
This paper cites Real-time optimal control of high- dimensional parametrized systems by deep learning-based reduced order models,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Real-time optimal control of high- dimensional parametrized systems by deep learning-based reduced order models,
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.894101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 84dd3c67-17f3-46dd-ae8e-ca37c793d5e0 · outbound
This paper cites A hybrid conv-lstm network with skip connections for nonlinear reduced-order modeling of spatiotemporal flow fields,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A hybrid conv-lstm network with skip connections for nonlinear reduced-order modeling of spatiotemporal flow fields,
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.875766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d7070b2e-b79e-4bb2-bdf1-c25217eb7985 · outbound
This paper cites Fractal invariance-constrained deep learning for spatial-temporal prediction of turbulent flows,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates Fractal invariance-constrained deep learning for spatial-temporal prediction of turbulent flows,
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:54.856489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6eb94905-349f-4aff-9fc5-636d6c88d3bb · outbound
This paper cites A deep learning approach to reduced order modelling of parameter dependent partial differential equations,.
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates A deep learning approach to reduced order modelling of parameter dependent partial differential equations,
Reference 61
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-15T14:18:54.564814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.