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We propose conformal generative modeling, a framework for generative modeling on 2D surfaces approximated by discrete triangle meshes.
Poisson surface reconstruction
Kazhdan, M., Bolitho, M., and Hoppe, H · 2006
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3d surface matching and recognition using conformal geometry
Wang, S., Wang, Y., Jin, M., Gu, X., and Samaras, D · 2006
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Ffts on the rotation group
Kostelec, P. J. and Rockmore, D. N · 2008
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A tutorial on conformal prediction
Shafer, G. and Vovk, V · 2008
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Conformal equivalence of triangle meshes
Springborn, B., Schröder, P., and Pinkall, U · 2008
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Manifold modeling for brain population analysis
Gerber, S., Tasdizen, T., Fletcher, P. T., Joshi, S., Whitaker, R., Initiative, A. D. N., et al · 2010
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A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions
Shapovalov, M. V. and Dunbrack Jr, R. L · 2011
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Triangulated manifold meshing method preserving molecular surface topology
Chen, M., Tu, B., and Lu, B · 2012
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Rigid motion estimation using mixtures of projected gaussians
Feiten, W., Lang, M., and Hirche, S · 2013
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Variational inference with normalizing flows
Rezende, D. and Mohamed, S · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Discrete conformal maps: Boundary value problems, circle domains, fuchsian and schottky uniformization
Bobenko, A. I., Sechelmann, S., and Springborn, B · 2016
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Density estimation using real nvp
Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2016
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Möbius registration
Baden, A., Crane, K., and Kazhdan, M · 2018
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Neural ordinary differential equations
Chen, R. T., Rubanova, Y., Bettencourt, J., and Duvenaud, D. K · 2018
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Contactdb: Analyzing and predicting grasp contact via thermal imaging
Brahmbhatt, S., Ham, C., Kemp, C. C., and Hays, J · 2019
Deepgem: Generalized expectation-maximization for blind inversion
Gao, A., Castellanos, J., Yue, Y., Ross, Z., and Bouman, K · 2021
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Discrete conformal equivalence of polyhedral surfaces
Gillespie, M., Springborn, B., and Crane, K · 2021
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Equivariant manifold flows
Katsman, I., Lou, A., Lim, D., Jiang, Q., Lim, S. N., and De Sa, C. M · 2021
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Normalizing flows for probabilistic modeling and inference
Papamakarios, G., Nalisnick, E. T., Rezende, D. J., Mohamed, S., and Lakshminarayanan, B · 2021
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Tractable density estimation on learned manifolds with conformal embedding flows
Ross, B. and Cresswell, J · 2021
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Moser flow: Divergence-based generative modeling on manifolds
Rozen, N., Grover, A., Nickel, M., and Lipman, Y · 2021
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Flows for simultaneous manifold learning and density estimation
Brehmer, J. and Cranmer, K · 2020
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Conformal Geometry of Simplicial Surfaces
Crane, K · 2020
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Neural manifold ordinary differential equations
Lou, A., Lim, D., Katsman, I., Huang, L., Jiang, Q., Lim, S. N., and De Sa, C. M · 2020
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Riemannian continuous normalizing flows
Mathieu, E. and Nickel, M · 2020
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Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
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Solving inverse problems in medical imaging with score-based generative models
Song, Y., Shen, L., Xing, L., and Ermon, S · 2021
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Riemannian score-based generative modeling
De Bortoli, V., Mathieu, E., Hutchinson, M., Thornton, J., Teh, Y. W., and Doucet, A · 2022
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A general recipe for likelihood-free bayesian optimization
Song, J., Yu, L., Neiswanger, W., and Ermon, S · 2022
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Riemannian flow matching on general geometries
Chen, R. T. and Lipman, Y · 2023
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