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Results: 8
Number of items: 8
  • Open Access
    Hoogeboom, E. (2023). Normalizing flows and diffusion models for discrete and geometric data. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Forre, P., Hoogeboom, E., Jaini, P., Nielsen, D., & Welling, M. (2022). Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6-14 December 2021 (Vol. 15, pp. 12454-12465). (Advances in Neural Information Processing Systems; Vol. 34). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2021/hash/67d96d458abdef21792e6d8e590244e7-Abstract.html
  • Open Access
    Hoogeboom, E., Garcia Satorras, V., Tomczak, J., & Welling, M. (2021). The Convolution Exponential and Generalized Sylvester Flows. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 22, pp. 18249-18248). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/d3f06eef2ffac7faadbe3055a70682ac-Abstract.html
  • Open Access
    Keller, T. A., Peters, J. W. T., Jaini, P., Hoogeboom, E., Forré, P., & Welling, M. (2021). Self Normalizing Flows. Proceedings of Machine Learning Research, 139, 5378-5387. https://arxiv.org/abs/2011.07248
  • Open Access
    Garcia Satorras, V., Hoogeboom, E., & Welling, M. (2021). E(n) Equivariant Graph Neural Networks. Proceedings of Machine Learning Research, 139, 9323-9332. https://proceedings.mlr.press/v139/satorras21a.html
  • Open Access
    Nielsen, D., Jaini, P., Hoogeboom, E., Winther, O., & Welling, M. (2021). SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 16, pp. 12685-12696). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/9578a63fbe545bd82cc5bbe749636af1-Abstract.html
  • Open Access
    Hoogeboom, E., Peters, J. W. T., van den Berg, R., & Welling, M. (2020). Integer Discrete Flows and Lossless Compression. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019 (Vol. 16, pp. 12114-12124). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/9e9a30b74c49d07d8150c8c83b1ccf07-Abstract.html
  • Open Access
    Hoogeboom, E., van den Berg, R., & Welling, M. (2019). Emerging Convolutions for Generative Normalizing Flows. Proceedings of Machine Learning Research, 97, 2771-2780. http://proceedings.mlr.press/v97/hoogeboom19a.html
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