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4966 Publications
2018 | Conference Paper | IST-REx-ID: 14202 | 
Locatello, F., Dresdner, G., Khanna, R., Valera, I., & Rätsch, G. (2018). Boosting black box variational inference. In Advances in Neural Information Processing Systems (Vol. 31). Montreal, Canada: Neural Information Processing Systems Foundation.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14201 |
Locatello, F., Khanna, R., Ghosh, J., & Rätsch, G. (2018). Boosting variational inference: An optimization perspective. In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (Vol. 84, pp. 464–472). Playa Blanca, Lanzarote: ML Research Press.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14198 |
Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., & Rätsch, G. (2018). SOM-VAE: Interpretable discrete representation learning on time series. In International Conference on Learning Representations. New Orleans, LA, United States.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14203 |
Yurtsever, A., Fercoq, O., Locatello, F., & Cevher, V. (2018). A conditional gradient framework for composite convex minimization with applications to semidefinite programming. In Proceedings of the 35th International Conference on Machine Learning (Vol. 80, pp. 5727–5736). Stockholm, Sweden: ML Research Press.
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| arXiv
2018 | Journal Article | IST-REx-ID: 282 |
Sachdeva, H., & Barton, N. H. (2018). Introgression of a block of genome under infinitesimal selection. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.118.301018
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