\begin{thebibliography}{59}
\providecommand{\natexlab}[1]{#1}
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  \providecommand{\doi}[1]{doi: #1}\else
  \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi

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\newblock Optimization and generation in aerodynamics inverse design.
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\newblock Microdreamer: Efficient 3d generation in ~20 seconds by score-based iterative reconstruction.
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\newblock Diffusion posterior sampling for general noisy inverse problems.
\newblock In \emph{11th International Conference on Learning Representations, ICLR 2023}, 2023.

\bibitem[Derksen \& Kemper(2002)Derksen and Kemper]{derksenComputationalInvariantTheory2002}
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\newblock Adjoint matching: Fine-tuning flow and diffusion generative models with memoryless stochastic optimal control.
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\newblock Taming text-to-sounding video generation via advanced modality condition and interaction.
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\bibitem[Guillemin \& Pollack(1974)Guillemin and Pollack]{guilleminDifferentialTopology1974}
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\bibitem[Hiller(1986)]{hillerCrystallographyCohomologyGroups1986}
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\bibitem[Humphreys(1992)]{humphreysReflectionGroupsCoxeter1992}
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\newblock Crystal structure prediction by joint equivariant diffusion.
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\newblock Space group constrained crystal generation.
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\newblock Symmcd: symmetry-preserving crystal generation with diffusion models.
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\bibitem[Li et~al.(2016)Li, Chen, Liu, and Tong]{liStructuralTopologyOptimization2016}
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\newblock Structural topology optimization considering connectivity constraint.
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\newblock One path to model them all: Learnable-time flow matching for crystal structure and energy prediction.
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\end{thebibliography}