Dr. P.D. (Patrick) Forré
Faculty of Science
Informatics Institute
Visiting address
- Science Park 904
- Room number:C3.226
Postal address
- Postbus 94323
1090 GH Amsterdam
Contact details
-
Publications
2020
Apostol, A. C., Stol, M. C., & Forré, P. (2020). FlipOut: Uncovering Redundant Weights via Sign Flipping. In L. Cao, W. Kosters, & J. Lijffijt (Eds.), BNAIC/BeNeLearn 2020: proceedings : Leiden, the Netherlands, November 19-20, 2020 (pp. 15-29). Universiteit Leiden. http://bnaic.liacs.leidenuniv.nl/wordpress/wp-content/uploads/papers/BNAICBENELEARN_2020_Final_paper_25.pdf [details]
2019
- Falorsi, L., de Haan, P., Davidson, T. R., & Forré, P. (2019). Reparameterizing Distributions on Lie Groups. Proceedings of Machine Learning Research, 89, 3244-3253. https://arxiv.org/abs/1903.02958 [details]
- Forré, P., & Mooij, J. M. (2019). Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 [15] AUAI Press. http://auai.org/uai2019/proceedings/papers/15.pdf [details]
- Patrini, G., van den Berg, R., Forré, P., Carioni, M., Bhargav, S., Welling, M., ... Nielsen, F. (2019). Sinkhorn AutoEncoders. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 [253] Corvallis, OR: AUAI Press. [details]
2018
- Forré, P., & Mooij, J. M. (2018). Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders. In A. Globerson, & R. Silva (Eds.), Uncertainty in Artificial Intelligence: proceedings of the Thirty-Fourth Concerence (2018) : August 6-10, 2018, Monterey, California, USA (pp. 269-278). AUAI Press. http://auai.org/uai2018/proceedings/papers/117.pdf [details]
2020
- Falorsi, L., & Forré, P. D. (2020). Neural Ordinary Differential Equations on Manifolds. Paper presented at ICML 2020 workshop INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, . https://arxiv.org/abs/2006.06663
- Federici, M., Dutta, A., Forré, P., Kushman, N., & Akata, Z. (2020). Learning Robust Representations via Multi-View Information Bottleneck. Paper presented at 8th International Conference on Learning Representations, Addis Abeba, Ethiopia.
- Keller, T. A., Peters, J. W. T., Jaini, P., Hoogeboom, E., Forré, P. D., & Welling, M. (2020). Self Normalizing Flows. Paper presented at NeurIPS 2020 workshop: Beyond BackPropagation: Novel Ideas for Training Neural Architectures, . https://arxiv.org/abs/2011.07248
2018
2020
- Bongers, S., Forré, P., Peters, J., Schölkopf, B., & Mooij, J. M. (2020). Foundations of Structural Causal Models with Cycles and Latent Variables. (v4 ed.) arXiv.org. https://arxiv.org/abs/1611.06221v4 [details]
- Helwegen, R., Louizos, C., & Forré, P. (2020). Improving Fair Predictions Using Variational Inference In Causal Models. (v1 ed.) arXiv.org. https://arxiv.org/abs/2008.10880 [details]
- Ilse, M., Tomczak, J. M., & Forré, P. (2020). Selecting Data Augmentation for Simulating Interventions. (v4 ed.) arXiv.org. https://arxiv.org/abs/2005.01856 [details]
- Verdenius, S., Stol, M., & Forré, P. (2020). Pruning via Iterative Ranking of Sensitivity Statistics. (v2 ed.) arXiv.org. https://arxiv.org/abs/2006.00896 [details]
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Ancillary activities
- No ancillary activities
Apostol, A. C., Stol, M. C., & Forré, P. (2020). FlipOut: Uncovering Redundant Weights via Sign Flipping. In L. Cao, W. Kosters, & J. Lijffijt (Eds.), BNAIC/BeNeLearn 2020: proceedings : Leiden, the Netherlands, November 19-20, 2020 (pp. 15-29). Universiteit Leiden.