Physics-Informed Modeling for Wood Thermal Analysis and Prediction | Paper Citation Record

Observation 11df41b9-17bb-430f-8c9e-93c590cb658d · outbound

This paper cites Automatic differentiation in machine learning: a survey.Journal of machine learning research, 18(153):1–43, 2018.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Automatic differentiation in machine learning: a survey.Journal of machine learning research, 18(153):1–43, 2018

Reference 1

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Observation 599d3bb5-20c8-463a-a798-8b43bc5017eb · outbound

This paper cites Physics-informed neural networks (pinns) for fluid mechanics: A review.Acta Mechanica Sinica, 37(12):1727–1738, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-informed neural networks (pinns) for fluid mechanics: A review.Acta Mechanica Sinica, 37(12):1727–1738, 2021

Reference 2

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Observation 83b3f597-f38b-4dec-829f-3c0ab332cd2a · outbound

This paper cites Physics-informed neural networks for heat transfer problems.Journal of Heat Transfer, 143(6):060801, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-informed neural networks for heat transfer problems.Journal of Heat Transfer, 143(6):060801, 2021

Reference 3

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This paper cites Cengel.Heat and mass transfer : a practical approach.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Cengel.Heat and mass transfer : a practical approach

Reference 4

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Observation 02eb029b-95d4-4f50-8f9b-3e02c341bccf · outbound

This paper cites Physics-informed learning of governing equations from scarce data.Nature communications, 12(1):6136, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-informed learning of governing equations from scarce data.Nature communications, 12(1):6136, 2021

Reference 5

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Observation b865db79-3e35-49a9-9a12-255c8839cd7b · outbound

This paper cites Multifunctional mesostructures: design and material programming for 4d-printing.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Multifunctional mesostructures: design and material programming for 4d-printing

Reference 6

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Observation 54287b0c-7151-42d3-ab4d-2622dabeed7a · outbound

This paper cites Deep thermal imaging: Proximate material type recognition in the wild through deep learning of spatial surface temperature patterns.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Deep thermal imaging: Proximate material type recognition in the wild through deep learning of spatial surface temperature patterns

Reference 7

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Observation 11b1775a-342f-4237-8567-47dfc910467b · outbound

This paper cites Thermal spread functions (tsf): Physics-guided material classification.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Thermal spread functions (tsf): Physics-guided material classification

Reference 8

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Observation 9f065796-6c10-4761-80d1-c42ec68f4407 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-04T10:29:45.075939Z

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Observation 17864cec-35bc-490c-bed7-082949a5517e · outbound

This paper cites Methods for the prediction and specification of functionally graded multi-grain responsive timber composites.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Methods for the prediction and specification of functionally graded multi-grain responsive timber composites

Reference 10

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Observation dc3499b2-de66-402c-ba8e-90bac57bb39a · outbound

This paper cites Wood-based responsive systems: a workflow for simulating, predicting and steering material performance in architectural design.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Wood-based responsive systems: a workflow for simulating, predicting and steering material performance in architectural design

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation f95fd6ea-105b-4b1d-adc2-ee8b7ec371ba · outbound

This paper cites Thermodynamic architectural surfaces: An in- tegrative modeling method for thermal design of wood and pcm lightweight structures.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Thermodynamic architectural surfaces: An in- tegrative modeling method for thermal design of wood and pcm lightweight structures

Reference 12

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Observation 1183313c-c45d-472a-98f4-2b6634107894 · outbound

This paper cites Predictive information model- ing: machine learning strategies for material uncertainty.Technology| Architecture+ Design, 5(2):163–176, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Predictive information model- ing: machine learning strategies for material uncertainty.Technology| Architecture+ Design, 5(2):163–176, 2021

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation 99e25d32-972d-4381-a064-d6559c7c13e1 · outbound

This paper cites Deep convolutional ritz method: parametric pde surrogates without la- beled data.Applied Mathematics and Mechanics, 44(7):1151–1174, 2023.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Deep convolutional ritz method: parametric pde surrogates without la- beled data.Applied Mathematics and Mechanics, 44(7):1151–1174, 2023

Reference 14

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This paper cites an unresolved cited work.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

Reference 15

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Observation 4b3cc4e0-8e71-46e5-b8c6-e83d02adaf41 · outbound

This paper cites Improving remote material classification ability with thermal imagery.Scientific Reports, 12(1):17288, 2022.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Improving remote material classification ability with thermal imagery.Scientific Reports, 12(1):17288, 2022

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation f5e4e66b-e385-4a8e-81c9-62cb7adfe356 · outbound

This paper cites Deep learning methodology for the identification of wood species using high-resolution macroscopic images.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Deep learning methodology for the identification of wood species using high-resolution macroscopic images

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation cde39b16-7770-4c15-8342-fce4dc8e6fcc · outbound

This paper cites The significance probability of the smirnov two-sample test.Arkiv för matematik, 3(5):469–486, 1958.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction The significance probability of the smirnov two-sample test.Arkiv för matematik, 3(5):469–486, 1958

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation 15ad4cc6-8f08-4899-8053-5c7bfe08b251 · outbound

This paper cites Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review.Plant Meth- ods, 17(1):47, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review.Plant Meth- ods, 17(1):47, 2021

Reference 19

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Observation 8e037872-15c1-453c-9688-62531655b456 · outbound

This paper cites Batch normalization: accelerating deep network training by reducing internal covariate shift.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Batch normalization: accelerating deep network training by reducing internal covariate shift

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

Reference 21

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Observation 82821b26-13fd-43ec-9939-2fa61beea957 · outbound

This paper cites Microgeometry capture using an elastomeric sensor.ACM Transactions on Graphics (TOG), 30(4): 1–8, 2011.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Microgeometry capture using an elastomeric sensor.ACM Transactions on Graphics (TOG), 30(4): 1–8, 2011

Reference 22

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Observation c901c4d6-fdc6-4b46-867b-f572ee01a7df · outbound

This paper cites Fine- grained material classification using micro-geometry and reflectance.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Fine- grained material classification using micro-geometry and reflectance

Reference 23

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Observation f044fce0-8730-43d0-823e-2b6be85fc40c · outbound

This paper cites Physics-informed machine learning.Nature Reviews Physics, 3(6): 422–440, 2021.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-informed machine learning.Nature Reviews Physics, 3(6): 422–440, 2021

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Observation 47d66ad7-8b3b-4e84-bdce-6ee9d1873989 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Adam: A Method for Stochastic Optimization

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-07-04T10:29:45.081414Z

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Observation 8ef4a465-a784-44f5-9c11-7c3d136f8982 · outbound

This paper cites Multi-resolution par- tial differential equations preserved learning framework for spatiotemporal dynamics.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Multi-resolution par- tial differential equations preserved learning framework for spatiotemporal dynamics

Reference 26

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Observation 19132f61-0074-4e11-aa82-a9a04dc90579 · outbound

This paper cites The kolmogorov-smirnov test for goodness of fit.Journal of the American statistical Association, 46(253):68–78, 1951.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction The kolmogorov-smirnov test for goodness of fit.Journal of the American statistical Association, 46(253):68–78, 1951

Reference 27

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Observation 3b0aa598-6ca4-45bb-8c4a-24efd9379e05 · outbound

This paper cites Performative wood: physically programming the responsive architecture of the hygroscope and hygroskin projects.Architectural Design, 85(5):66–73, 2015.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Performative wood: physically programming the responsive architecture of the hygroscope and hygroskin projects.Architectural Design, 85(5):66–73, 2015

Reference 28

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Observation de469286-5cf4-4675-9517-0189bdfc609e · outbound

This paper cites Siboni, and Dierk Raabe.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Siboni, and Dierk Raabe

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Observation f6d6c9be-8084-4f3c-b3fe-747d2e788468 · outbound

This paper cites Embed- ding hard physical constraints in neural network coarse-graining of three-dimensional turbulence.Physical Review Fluids, 8(1):014604, 2023.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Embed- ding hard physical constraints in neural network coarse-graining of three-dimensional turbulence.Physical Review Fluids, 8(1):014604, 2023

Reference 30

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Observation d2fc8a07-8c7a-4878-8236-68560ddeae35 · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Rectified linear units improve restricted boltzmann machines

Reference 31

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Observation f90cc8b7-18f3-45d1-ad1d-d543eb5d843a · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.Advances in neural infor- mation processing systems, 32, 2019.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Pytorch: An imperative style, high-performance deep learning library.Advances in neural infor- mation processing systems, 32, 2019

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Observation 2423d954-c42e-4537-bedf-a4049a985808 · outbound

This paper cites Fully dif- ferentiable lagrangian convolutional neural network for physics-informed precipitation nowcasting.Applied Computing and Geosciences, page 100296, 2025.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Fully dif- ferentiable lagrangian convolutional neural network for physics-informed precipitation nowcasting.Applied Computing and Geosciences, page 100296, 2025

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Observation e243b8f2-b49d-4f4e-89bf-70eb51ec7663 · outbound

This paper cites Film: Visual reasoning with a general conditioning layer.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Film: Visual reasoning with a general conditioning layer

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Observation 7e4a46a3-7e25-4cf8-a7ec-1835a90b4bb9 · outbound

This paper cites Failing loudly: An em- pirical study of methods for detecting dataset shift.Advances in Neural Information Processing Systems, 32, 2019.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Failing loudly: An em- pirical study of methods for detecting dataset shift.Advances in Neural Information Processing Systems, 32, 2019

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Observation 160ce768-e6ae-4f40-9d19-8ec6ffdba548 · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

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Resolution: verified exact; local_arxiv, observed 2026-07-04T10:29:45.083944Z

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

Reference 38

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Encod- ing physics to learn reaction–diffusion processes.Nature Machine Intelligence, 5(7): 765–779, 2023

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Observation 05e50788-16ea-4f33-941c-45252174768f · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction U-net: Convolutional networks for biomedical image segmentation

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Observation 94e87c27-49cf-4c12-a412-f50f76dbcf53 · outbound

This paper cites Material classification with thermal imagery.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Material classification with thermal imagery

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Observation 7df65920-5f6a-4872-b474-62c31946d2fb · outbound

This paper cites A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction A Multimodal Physics-Informed Neural Network Approach for Mean Radiant Temperature Modeling

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Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:45.070987Z

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Observation 33a118bd-0e09-444c-85d5-009a26c10503 · outbound

This paper cites Computer vision- based wood identification: A review.Forests, 13(12):2041, 2022.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Computer vision- based wood identification: A review.Forests, 13(12):2041, 2022

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Observation 6bc14418-cfe3-4b48-b8e4-010170478838 · outbound

This paper cites DINOv3.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction DINOv3

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Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T10:29:45.073431Z

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Observation b1c0083b-2d92-4532-b3c0-81f4a5da813d · outbound

This paper cites Estimate of deviation between empirical distribution functions in two independent samples.Bulletin Moscow University, 2(2):3–16, 1939.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Estimate of deviation between empirical distribution functions in two independent samples.Bulletin Moscow University, 2(2):3–16, 1939

Reference 45

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Observation 14f1bc2b-a2ec-4920-9702-7de4065ebc1c · outbound

This paper cites Material classification from time-of-flight distortions.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Material classification from time-of-flight distortions

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Observation 586b8594-1cde-490f-949f-d491ae5ee2c0 · outbound

This paper cites Routledge, 2016.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Routledge, 2016

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Observation 42dfe1f2-f4e3-4749-9851-54a2aa73534c · outbound

This paper cites Spline-pinn: Approaching pdes without data using fast, physics-informed hermite-spline cnns.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Spline-pinn: Approaching pdes without data using fast, physics-informed hermite-spline cnns

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Observation ad59f98a-fb23-44ff-bc3a-c6701aa3d792 · outbound

This paper cites The applications of machine vision in raw material and production of wood products.BioResources, 17(3):5532, 2022.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction The applications of machine vision in raw material and production of wood products.BioResources, 17(3):5532, 2022

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Observation f659c518-f7e7-49ac-9a66-c009235b010e · outbound

This paper cites Physics-guided deep learning for dynamical systems: A survey.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-guided deep learning for dynamical systems: A survey

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Observation 65618684-f56b-43cf-929e-09e3777c4bb5 · outbound

This paper cites Fp64 is all you need: rethinking failure modes in physics-informed neural networks.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Fp64 is all you need: rethinking failure modes in physics-informed neural networks

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Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:45.078968Z

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Observation fa0697ee-4600-443e-a2e4-2cf687072a65 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Depth anything: Unleashing the power of large-scale unlabeled data

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Observation b94e5db0-c6bc-41a9-8a46-0aff78e1bcf9 · outbound

This paper cites Depth anything v2.Advances in Neural Information Processing Systems, 37:21875–21911, 2024.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Depth anything v2.Advances in Neural Information Processing Systems, 37:21875–21911, 2024

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Observation 101b2376-e659-4b5c-a56e-b8cea452b451 · outbound

This paper cites Learning dynamical systems from data: An introduction to physics-guided deep learning.Proceedings of the National Academy of Sciences, 121 (27):e2311808121, 2024.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Learning dynamical systems from data: An introduction to physics-guided deep learning.Proceedings of the National Academy of Sciences, 121 (27):e2311808121, 2024

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This paper cites Mrf-pinn: a multi-receptive- field convolutional physics-informed neural network for solving partial differential equations.Computational Mechanics, 75(3):1137–1163, 2025.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Mrf-pinn: a multi-receptive- field convolutional physics-informed neural network for solving partial differential equations.Computational Mechanics, 75(3):1137–1163, 2025

Reference 55

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Observation 9673d72e-8cee-4a1f-8940-cbe93e27cc59 · outbound

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation 72c694db-dcef-4406-9ef8-7ea23f84d301 · outbound

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Physics-Informed Modeling for Wood Thermal Analysis and Prediction Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation 7f040d3d-b244-4d6e-bb83-c6822ad94e76 · outbound

This paper cites Automated design for physics- informed modeling with convolutional neural networks.Communications Physics, 2025.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Automated design for physics- informed modeling with convolutional neural networks.Communications Physics, 2025

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-26T08:48:43.739928Z

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Observation 4352f77b-be61-4c69-9e3d-cf8d68c7b565 · outbound

This paper cites Physics-constrained deep learning for high-dimensional surrogate modeling and un- certainty quantification without labeled data.Journal of computational physics, 394: 56–81, 2019.

Physics-Informed Modeling for Wood Thermal Analysis and Prediction Physics-constrained deep learning for high-dimensional surrogate modeling and un- certainty quantification without labeled data.Journal of computational physics, 394: 56–81, 2019

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:45.077762Z

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