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Recently there has been growing interest in modeling sets with exchangeability such as point clouds.
Spectra of some self-exciting and mutually exciting point processes
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Learning representations and generative models for 3d point clouds
Achlioptas, P., Diamanti, O., Mitliagkas, I., and Guibas, L · 2017
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Learning scalable deep kernels with recurrent structure
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Doubly stochastic variational inference for deep gaussian processes
Salimbeni, H. and Deisenroth, M · 2017
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Deep determinantal point process for large-scale multi-label classification
Xie, P., Salakhutdinov, R., Mou, L., and Xing, E · 2017
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Zaheer, M., Kottur, S., Ravanbakhsh, S., Poczos, B., Salakhutdinov, R. R., and Smola, A. J · 2017
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Structure discovery in nonparametric regression through compositional kernel search
Duvenaud, D. K., Lloyd, J. R., Grosse, R. B., Tenenbaum, J. B., and Ghahramani, Z · 2013
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Gaussian processes for big data
Hensman, J., Fusi, N., and Lawrence, N. D · 2013
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2013
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Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D · 2014
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Student-t processes as alternatives to gaussian processes
Shah, A., Wilson, A., and Ghahramani, Z · 2014
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Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2015
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Multiresolution tree networks for 3d point cloud processing
Gadelha, M., Wang, R., and Maji, S · 2018
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BRUNO: A deep recurrent model for exchangeable data
Korshunova, I., Degrave, J., Huszar, F., Gal, Y., Gretton, A., and Dambre, J · 2018
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Li, C.-L., Zaheer, M., Zhang, Y., Poczos, B., and Salakhutdinov, R · 2018
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Variational implicit processes
Ma, C., Li, Y., and Hernández-Lobato, J. M · 2018
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Pointgrow: Autoregressively learned point cloud generation with self-attention
Sun, Y., Wang, Y., Liu, Z., Siegel, J. E., and Sarma, S. E · 2018
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Sparse and deep generalizations of the frame model
Wu, Y. N., Xie, J., Lu, Y., and Zhu, S.-C · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Yang, Y., Feng, C., Shen, Y., and Tian, D · 2018
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Exponential family estimation via adversarial dynamics embedding
Dai, B., Liu, Z., Dai, H., He, N., Gretton, A., Song, L., and Schuurmans, D · 2019
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Introduction to the theory of Gibbs point processes
Dereudre, D · 2019
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Implicit generation and generalization in energy-based models
Du, Y. and Mordatch, I · 2019
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Kim, H., Mnih, A., Schwarz, J., Garnelo, M., Eslami, A., Rosenbaum, D., Vinyals, O., and Teh, Y. W · 2019
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Neural similarity learning
Liu, W., Liu, Z., Rehg, J. M., and Song, L · 2019
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The functional neural process
Louizos, C., Shi, X., Schutte, K., and Welling, M · 2019
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Pointflow: 3d point cloud generation with continuous normalizing flows
Yang, G., Huang, X., Hao, Z., Liu, M.-Y., Belongie, S., and Hariharan, B · 2019
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Adversarial autoencoders for generating 3d point clouds
Zamorski, M., Zieba, M., Nowak, R., Stokowiec, W., and Trzcinski, T · 2019
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