TADALoT

Here is a list of publications related to the project (if you can't find the pdf e.g. from searching the title in google scholar, don't hesitate to contact us).

  1. [Alaverdyan MEDIA 2020] Alaverdyan, Z., Jung, J., Bouet, R., & Lartizien, C. (2020). Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: application to epilepsy lesion screening. Medical image analysis, 60, 101618.
  2. [Viola IJAIT 21] Viola, R., Emonet, R., Habrard, A., Metzler, G., Riou, S., & Sebban, M. (2019, November). A Nearest Neighbor Algorithm for Imbalanced Classification. In International Journal on Artificial Intelligence Tools (IJAIT), 2021.
  3. [Kerdoncuff MLJ 21] Kerdoncuff, T., Emonet, R., & Sebban, M. (2021). Sampled Gromov Wasserstein. Machine Learning, 110(8), 2151-2186.
  4. [Munoz-Ramirez MLCN 2021] Muñoz-Ramírez, V., Pinon, N., Forbes, F., Lartizen, C., & Dojat, M. (2021, September). Patch vs. global image-based unsupervised anomaly detection in MR brain scans of early Parkinsonian patients. In International Workshop on Machine Learning in Clinical Neuroimaging (pp. 34-43). Springer, Cham.
  5. [Zotova et al., SASHIMI 2021] Zotova, D., Jung, J., & Lartizien, C. (2021, September). GAN-Based Synthetic FDG PET Images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection Models. In International Workshop on Simulation and Synthesis in Medical Imaging (pp. 142-152). Springer, Cham.
  6. [Bascol AISTATS 19] Bascol, K., Emonet, R., Fromont, E., Habrard, A., Metzler, G., & Sebban, M. (2019, April). From cost-sensitive to tight f-measure bounds. In The 22nd International Conference on Artificial Intelligence and Statistics (pp. 1245-1253). PMLR.
  7. [Viola ICTAI 19] Viola, R., Emonet, R., Habrard, A., Metzler, G., Riou, S., & Sebban, M. (2019, November). An adjusted nearest neighbor algorithm maximizing the f-measure from imbalanced data. In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 243-250). IEEE.
  8. [Dhouib ICML 20a] Dhouib, S., Redko, I., Kerdoncuff, T., Emonet, R., & Sebban, M. (2020, November). A swiss army knife for minimax optimal transport. In International Conference on Machine Learning (pp. 2504-2513). PMLR.
  9. [Dhouib ICML 20b] Dhouib, S., Redko, I., & Lartizien, C. (2020, November). Margin-aware adversarial domain adaptation with optimal transport. In International Conference on Machine Learning (pp. 2514-2524). PMLR.
  10. [Kerdoncuff IJCAI 21] Kerdoncuff, T., Emonet, R., & Sebban, M. (2021, January). Metric learning in optimal transport for domain adaptation. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence (pp. 2162-2168).
  11. [Kerdoncuff AAAI 22] Kerdoncuff, T., Emonet, R., Perrot, M., & Sebban, M. (2022, June). Optimal Tensor Transport. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 7, pp. 7124-7132).