A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems | Paper Citation Record

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This paper cites Symplectic isotopy on non-minimal ruled surfaces.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Symplectic isotopy on non-minimal ruled surfaces

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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This paper cites Accelerating CFD simulation with high order finite difference method on curvilinear coordinates for modern GPU clusters.Advances in Aerodynamics, 4(1):7, February 2022.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Accelerating CFD simulation with high order finite difference method on curvilinear coordinates for modern GPU clusters.Advances in Aerodynamics, 4(1):7, February 2022

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This paper cites GPU-Accelerated Finite Element Method for Modelling Light Transport in Diffuse Optical Tomography.International Journal of Biomedical Imaging, 2011:403892, 2011.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems GPU-Accelerated Finite Element Method for Modelling Light Transport in Diffuse Optical Tomography.International Journal of Biomedical Imaging, 2011:403892, 2011

Reference 4

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This paper cites Tr¨ aff, Anton Rydahl, Sven Karlsson, Ole Sigmund, and Niels Aage.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Tr¨ aff, Anton Rydahl, Sven Karlsson, Ole Sigmund, and Niels Aage

Reference 5

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This paper cites Modular and flexible spectral-element waveform modelling in two and three dimensions.Geophysical Journal International, 216(3):1675–1692, March 2019.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Modular and flexible spectral-element waveform modelling in two and three dimensions.Geophysical Journal International, 216(3):1675–1692, March 2019

Reference 6

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This paper cites Generalized GPU Acceleration for Applications Employing Finite-Volume Meth- ods.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Generalized GPU Acceleration for Applications Employing Finite-Volume Meth- ods

Reference 7

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This paper cites MIT Press, 2016.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems MIT Press, 2016

Reference 8

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This paper cites Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Bishop and Hugh Bishop.Deep Learning: Foundations and Concepts

Reference 9

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This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 10

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This paper cites JAX: composable trans- formations of Python+NumPy programs, 2018.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems JAX: composable trans- formations of Python+NumPy programs, 2018

Reference 11

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This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 12

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This paper cites Springer Inter- national Publishing, Cham, 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Springer Inter- national Publishing, Cham, 2021

Reference 13

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This paper cites Deep learning in computational mechanics: a review.Com- putational Mechanics, January 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Deep learning in computational mechanics: a review.Com- putational Mechanics, January 2024

Reference 14

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This paper cites Neural network representation of finite element method.Neural Networks, 7 (2):389–395, January 1994.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Neural network representation of finite element method.Neural Networks, 7 (2):389–395, January 1994

Reference 15

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This paper cites Ramuhalli, L.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Ramuhalli, L

Reference 16

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This paper cites FEA-Net: A Deep Convolutional Neural Network With PhysicsPrior For Efficient Data Driven PDE Learning.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems FEA-Net: A Deep Convolutional Neural Network With PhysicsPrior For Efficient Data Driven PDE Learning

Reference 17

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This paper cites FEA-Net: A physics-guided data-driven model for efficient mechanical response prediction.Computer Methods in Applied Mechanics and Engineering, 363:112892, May 2020.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems FEA-Net: A physics-guided data-driven model for efficient mechanical response prediction.Computer Methods in Applied Mechanics and Engineering, 363:112892, May 2020

Reference 18

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This paper cites Apley, Gre- gory J.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Apley, Gre- gory J

Reference 19

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This paper cites Mishra and P.S.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Mishra and P.S

Reference 20

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This paper cites Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques

Reference 21

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This paper cites Innanen, Junxiao Li, and Daniel O.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Innanen, Junxiao Li, and Daniel O

Reference 22

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This paper cites On the use of neural networks for full waveform inversion.Computer Methods in Applied Mechanics and Engineering, 415:116278, October 2023.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems On the use of neural networks for full waveform inversion.Computer Methods in Applied Mechanics and Engineering, 415:116278, October 2023

Reference 23

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This paper cites Injective Hulls of Quantale-Enriched Multicategories.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Injective Hulls of Quantale-Enriched Multicategories

Reference 24

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This paper cites A tutorial on the adjoint method for inverse problems.Computer Methods in Applied Mechanics and Engineering, 380:113810, July 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems A tutorial on the adjoint method for inverse problems.Computer Methods in Applied Mechanics and Engineering, 380:113810, July 2021

Reference 27

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This paper cites Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation.Optimization Methods and Software, 1(1):35–54, January 1992.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation.Optimization Methods and Software, 1(1):35–54, January 1992

Reference 28

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 29

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 30

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This paper cites Anderson, Lijian Tan, and Don Wang.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Anderson, Lijian Tan, and Don Wang

Reference 31

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This paper cites Wavefield compression for 26 adjoint methods in full-waveform inversion.GEOPHYSICS, 81(6):R385–R397, 2016.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Wavefield compression for 26 adjoint methods in full-waveform inversion.GEOPHYSICS, 81(6):R385–R397, 2016

Reference 32

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This paper cites Herrmann.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Herrmann

Reference 33

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This paper cites High-performance xPU Stencil Computations in Julia.JuliaCon Proceedings, 6(64):138, October 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems High-performance xPU Stencil Computations in Julia.JuliaCon Proceedings, 6(64):138, October 2024

Reference 34

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This paper cites Distributed Parallelization of xPU Stencil Computations in Julia.JuliaCon Proceedings, 6(65):137, November 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Distributed Parallelization of xPU Stencil Computations in Julia.JuliaCon Proceedings, 6(65):137, November 2024

Reference 35

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This paper cites SeimicWaves.jl: an efficient yet user-friendly Julia package for Full-Waveform Inversion on multi-xPUs.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems SeimicWaves.jl: an efficient yet user-friendly Julia package for Full-Waveform Inversion on multi-xPUs

Reference 36

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This paper cites Clapp.Reverse time migration with random boundaries, pages 2809–2813.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Clapp.Reverse time migration with random boundaries, pages 2809–2813

Reference 37

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This paper cites Random boundary condition for memory-efficient waveform inversion gradient computation.GEOPHYSICS, 80:R351–R359, 11 2015.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Random boundary condition for memory-efficient waveform inversion gradient computation.GEOPHYSICS, 80:R351–R359, 11 2015

Reference 38

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This paper cites Inversion of seismic reflection data in the acoustic approximation.GEOPHYSICS, 49(8): 1259–1266, August 1984.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Inversion of seismic reflection data in the acoustic approximation.GEOPHYSICS, 49(8): 1259–1266, August 1984

Reference 39

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This paper cites Advances in Geophysical and Envi- ronmental Mechanics and Mathematics.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Advances in Geophysical and Envi- ronmental Mechanics and Mathematics

Reference 40

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This paper cites Topology optimization of an acoustic horn.Computer Methods in Applied Mechanics and Engineering, 196(1-3):420–436, December 2006.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Topology optimization of an acoustic horn.Computer Methods in Applied Mechanics and Engineering, 196(1-3):420–436, December 2006

Reference 41

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This paper cites Rigid body modeling issue in acoustical topology optimization.Computer Methods in Applied Mechanics and Engineering, 198(9-12):1017–1030, February 2009.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Rigid body modeling issue in acoustical topology optimization.Computer Methods in Applied Mechanics and Engineering, 198(9-12):1017–1030, February 2009

Reference 42

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This paper cites Minimization of sound radiation from vibrating bi-material structures using topology optimization.Structural and Multidisciplinary Optimization, 33(4-5):305–321, February 2007.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Minimization of sound radiation from vibrating bi-material structures using topology optimization.Structural and Multidisciplinary Optimization, 33(4-5):305–321, February 2007

Reference 43

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 44

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This paper cites D¨ uhring, Jakob S.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems D¨ uhring, Jakob S

Reference 45

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This paper cites Jensen, and Semyung Wang.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Jensen, and Semyung Wang

Reference 46

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This paper cites Jensen and O.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Jensen and O

Reference 47

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This paper cites Christiansen and Ole Sigmund.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Christiansen and Ole Sigmund

Reference 48

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This paper cites Christiansen and Ole Sigmund.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Christiansen and Ole Sigmund

Reference 49

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correction dated 2021-05-10. Source: crossref record 10.1364/josab.427899->10.1364/josab.405955:correction, observed 2026-07-11T03:01:41.953179+00:00. This notice travels one citation hop only.

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This paper cites Scalable parallel programming with CUDA.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Scalable parallel programming with CUDA

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This paper cites A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems [Software], September.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems [Software], September

Reference 51

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This paper cites Adam: A Method for Stochastic Optimization.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Adam: A Method for Stochastic Optimization

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This paper cites Liu and Jorge Nocedal.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Liu and Jorge Nocedal

Reference 53

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This paper cites The method of moving asymptotes—a new method for structural optimization.International Journal for Numerical Methods in Engineering, 24(2):359–373, February 1987.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems The method of moving asymptotes—a new method for structural optimization.International Journal for Numerical Methods in Engineering, 24(2):359–373, February 1987

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Observation 8461fe14-46f7-48d0-8690-643da1660478 · outbound

This paper cites Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Ev- 27 geni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, St´ efan J.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Ev- 27 geni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, St´ efan J

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.323491Z

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Observation e820fde6-475f-4108-8251-7e65ed3c6079 · outbound

This paper cites Immersed boundary parametrizations for full waveform inversion.Computer Methods in Applied Mechanics and Engineering, 406:115893, March.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Immersed boundary parametrizations for full waveform inversion.Computer Methods in Applied Mechanics and Engineering, 406:115893, March

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.327695Z

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Observation c90b1256-1ab9-4682-8913-acdc1165c8c8 · outbound

This paper cites Fichtner, H.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Fichtner, H

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.334690Z

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Observation a8fcb144-756f-48c2-af30-55a615c18524 · outbound

This paper cites Fichtner, H.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Fichtner, H

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Resolution: verified exact; doi, observed 2026-08-15T15:55:52.981797Z

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Observation 782e6155-f9d9-4d55-9781-b322021960ef · outbound

This paper cites Isogeometric multi-resolution full waveform inversion based on the finite cell method.Computer Methods in Applied Mechanics and Engineering, 417:116286, December 2023.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Isogeometric multi-resolution full waveform inversion based on the finite cell method.Computer Methods in Applied Mechanics and Engineering, 417:116286, December 2023

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.341864Z

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Observation 62e48a26-b956-456e-a804-41f0bca3bb4f · outbound

This paper cites Solving inverse problems using data-driven models.Acta Numerica, 28:1–174, May 2019.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Solving inverse problems using data-driven models.Acta Numerica, 28:1–174, May 2019

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 53279b95-d66f-4fc1-bdd8-52e4a9289858 · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.349093Z

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Observation 503791f7-dc66-4f2a-86f0-64189654671d · outbound

This paper cites On projection methods, convergence and robust formulations in topology optimization.Structural and Multidisciplinary Optimization, 43(6):767–784, June.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems On projection methods, convergence and robust formulations in topology optimization.Structural and Multidisciplinary Optimization, 43(6):767–784, June

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.352875Z

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Observation 99a2f21e-8f63-4c18-8c28-80967bf0924c · outbound

This paper cites Volume preserving projection filters and continuation methods in topology optimization.Engineering Structures, 85:144–161, February 2015.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Volume preserving projection filters and continuation methods in topology optimization.Engineering Structures, 85:144–161, February 2015

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Resolution: malformed identifier; no resolver link, observed 2026-08-15T15:55:52.360090Z

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Observation f19cf8c9-c3c4-440b-bf99-ad70f89ba97c · outbound

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.363564Z

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Observation d3a10f30-4973-4097-aee0-93572e9e8595 · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.367332Z

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Observation f491cfbb-5133-4668-a444-e2dea73d0add · outbound

This paper cites Bendsøe and O.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Bendsøe and O

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.371052Z

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Observation dbb5e288-b3c3-421b-b407-a78e801888d9 · outbound

This paper cites Alicia Kim.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Alicia Kim

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Resolution: verified exact; doi, observed 2026-08-15T15:55:52.726865Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9b3726a8-1a16-45d2-b140-97755dafa7b6 · outbound

This paper cites Dilgen and Niels Aage.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Dilgen and Niels Aage

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.378552Z

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Observation 3df1c89b-41a7-4eb7-8aab-8aa12f894a6a · outbound

This paper cites Conlon, and Fabio Semperlotti.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Conlon, and Fabio Semperlotti

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Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T15:55:53.646390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 53f10427-4660-4031-aa31-1e6eabe2545a · outbound

This paper cites Topology optimization of a waveguide acoustic black hole for enhanced wave focusing.The Journal of the Acoustical Society of America, 155(1): 742–756, January 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Topology optimization of a waveguide acoustic black hole for enhanced wave focusing.The Journal of the Acoustical Society of America, 155(1): 742–756, January 2024

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4df074bf-7b38-4906-8fe8-2ddda5e97b1a · outbound

This paper cites On neu- ral networks for generating better local optima in topology optimization.Structural and Multidisciplinary 28 Optimization, 67(11):192, November 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems On neu- ral networks for generating better local optima in topology optimization.Structural and Multidisciplinary 28 Optimization, 67(11):192, November 2024

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a0c95c74-4c82-4117-8768-32667a9bd49e · outbound

This paper cites Sigmund and J.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Sigmund and J

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.392584Z

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Observation d06e9a63-c2ad-49fc-b692-d074294ce883 · outbound

This paper cites Bruns and Daniel A.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Bruns and Daniel A

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Observation dd7660c5-36db-459b-b265-29018f43eaa6 · outbound

This paper cites Filters in topology optimization.International Journal for Numerical Methods in Engineering, 50(9):2143–2158, March 2001.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Filters in topology optimization.International Journal for Numerical Methods in Engineering, 50(9):2143–2158, March 2001

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Observation f6283303-9ecc-4708-9f89-37ac499d104e · outbound

This paper cites Lazarov, and Ole Sigmund.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Lazarov, and Ole Sigmund

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Observation 9c544ba4-cf29-48f5-95a1-1264d4b1db66 · outbound

This paper cites Christiansen, Boyan S.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Christiansen, Boyan S

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Resolution: malformed identifier; doi_truncated, observed 2026-08-15T15:55:52.669325Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3c28a9c4-affe-44de-832e-4524994b54a0 · outbound

This paper cites Morphology-based black and white filters for topology optimization.Structural and Multidis- ciplinary Optimization, 33(4):401–424, April 2007.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Morphology-based black and white filters for topology optimization.Structural and Multidis- ciplinary Optimization, 33(4):401–424, April 2007

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Source-reported events for the cited work

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Observation 23489e15-0a64-4471-a71f-ee2e50e473d4 · outbound

This paper cites Manufacturing tolerant topology optimization.Acta Mechanica Sinica, 25(2):227–239, April 2009.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Manufacturing tolerant topology optimization.Acta Mechanica Sinica, 25(2):227–239, April 2009

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.414617Z

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Observation d736a886-4780-4821-b8a9-46208055bf78 · outbound

This paper cites Springer International Publish- ing, Cham, 2017.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Springer International Publish- ing, Cham, 2017

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.418392Z

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Observation 5356c24a-ed50-4260-8b9b-d49e143a41e5 · outbound

This paper cites On the Use of Neural Networks for Full Waveform Inversion [Software], August 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems On the Use of Neural Networks for Full Waveform Inversion [Software], August 2024

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.421673Z

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Observation 9d6881c1-4a01-48e1-ae8a-447e45980535 · outbound

This paper cites The inverse crime, January 2004.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems The inverse crime, January 2004

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Resolution: verified exact; raw_fallback, observed 2026-08-15T15:55:53.567199Z

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Observation ed1274cf-55f8-4dde-9476-e046178700f8 · outbound

This paper cites Lecture notes on inverse theory, 07 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Lecture notes on inverse theory, 07 2021

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.429635Z

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Observation 0246d5d7-2d8a-43fc-9b6e-467841cba859 · outbound

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 83

Resolution: verified exact; doi, observed 2026-08-15T15:55:52.636793Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f62f659e-9aa4-4b51-a15b-0d6ce353f593 · outbound

This paper cites Finite cell method.Computational Mechanics, 41(1): 121–133, December 2007.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Finite cell method.Computational Mechanics, 41(1): 121–133, December 2007

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Observation cf8004ec-4d55-49d8-8e15-81563ab2275a · outbound

This paper cites The\textlessspan style=”font-variant:small- caps;”\textgreaterp\textless/span\textgreater -Version of the Finite Element and Finite Cell Methods.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems The\textlessspan style=”font-variant:small- caps;”\textgreaterp\textless/span\textgreater -Version of the Finite Element and Finite Cell Methods

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Resolution: verified exact; doi, observed 2026-08-15T15:55:52.618047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e830f094-ecf5-4a6f-80d0-9d7ea94b46e2 · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.444352Z

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Observation 3d0dd1be-54a8-4c4d-8853-89c6032c28ae · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.447912Z

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Observation e1fe3a91-35aa-4af3-9cd1-eede0b429ada · outbound

This paper cites Attention is All you Need.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Attention is All you Need

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.451463Z

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Observation 64cd0d61-cfd0-4cfe-9827-d31bf0233a75 · outbound

This paper cites Compute Trends Across Three Eras of Machine Learning.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Compute Trends Across Three Eras of Machine Learning

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Observation 7ae247d0-b0cb-4ab4-a6ee-efc273ce2ccb · outbound

This paper cites The Neural Network Approach to Inverse Problems in Differential Equations.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems The Neural Network Approach to Inverse Problems in Differential Equations

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Observation cfbdf9d9-c8d6-46b9-ba54-c54a246efa50 · outbound

This paper cites Neural networks as smooth priors for inverse problems for PDEs.Journal of Computational Mathematics and Data Science, 1:100008, September 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Neural networks as smooth priors for inverse problems for PDEs.Journal of Computational Mathematics and Data Science, 1:100008, September 2021

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Observation d087701d-4738-4b4a-9ac9-ded1b6a0839b · outbound

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A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.464980Z

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Observation 5ccf1c6f-48bc-4222-a0fb-4c5987594ba3 · outbound

This paper cites Full waveform inversion based on 29 inversion network reparameterized velocity.Geophysical Prospecting, 72(1):52–67, January 2024.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Full waveform inversion based on 29 inversion network reparameterized velocity.Geophysical Prospecting, 72(1):52–67, January 2024

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3930ac1e-3b70-4d11-88f4-49381cd26144 · outbound

This paper cites Accelerating full waveform inversion by transfer learning.Computational Mechanics, February 2025.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Accelerating full waveform inversion by transfer learning.Computational Mechanics, February 2025

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1e840459-9c3e-44ff-9e3d-1e65beea0383 · outbound

This paper cites Deep Reparameterization for Full Waveform Inversion: Architecture Benchmarking, Robust Inversion, and Multiphysics Extension.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Deep Reparameterization for Full Waveform Inversion: Architecture Benchmarking, Robust Inversion, and Multiphysics Extension

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Observation f6ea7176-e647-4364-9726-9f659568919d · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.478705Z

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Observation cc18b09e-68b4-47aa-bd2d-206fff64f18f · outbound

This paper cites Neural reparameterization improves structural optimization.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Neural reparameterization improves structural optimization

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Observation c413b118-9032-4bc9-b1f9-d84bfb229385 · outbound

This paper cites an unresolved cited work.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-15T15:55:52.489205Z

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Unavailable: canonical work link unavailable.

Observation 859ca47e-3bc5-4a5c-8c3c-4f5eb64693f8 · outbound

This paper cites A New Topology Optimization Approach by Physics-Informed Deep Learning Process.Advances in Science, Technology and Engineering Systems Journal, 6(4):233–240, July 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems A New Topology Optimization Approach by Physics-Informed Deep Learning Process.Advances in Science, Technology and Engineering Systems Journal, 6(4):233–240, July 2021

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Observation 56e13f6a-510f-4a8a-b559-ad58e2725d83 · outbound

This paper cites TOuNN: Topology Optimization using Neural Networks.Struc- tural and Multidisciplinary Optimization, 63(3):1135–1149, March 2021.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems TOuNN: Topology Optimization using Neural Networks.Struc- tural and Multidisciplinary Optimization, 63(3):1135–1149, March 2021

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Unavailable: canonical work link unavailable.

Observation 32bd2692-72ea-47e7-be5b-d4d45708503a · outbound

This paper cites Multi-Material Topology Optimization Using Neural Networks.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Multi-Material Topology Optimization Using Neural Networks

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Observation 6f333a21-0b1d-4613-a919-59b7dd3b3f01 · outbound

This paper cites Approximate Length Scale Filter in Topology Optimization using Fourier Enhanced Neural Networks.Computer-Aided Design, 150:103277, September 2022.

A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems Approximate Length Scale Filter in Topology Optimization using Fourier Enhanced Neural Networks.Computer-Aided Design, 150:103277, September 2022

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