![]() | Up a level |
This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Anbil Parthipan, S. C., Khapra, M. M., Larochelle, H., & Ravindran, B. (2016). Correlational Neural Networks. Neural Computation, 28(2), 257-285. External link
Anbil Parthipan, S. C., Lauly, S., Larochelle, H., Khapra, M. M., Ravindran, B., Raykar, V., & Saha, A. (2014, December). An autoencoder approach to learning bilingual word representations [Paper]. 27th International Conference on Neural Information Processing Systems, Montréal, Qc, Canada. External link
Bard, N., Foerster, J. N., Anbil Parthipan, S. C., Burch, N., Lanctot, M., Song, H. F., Parisotto, E., Dumoulin, V., Moitra, S., Hughes, E., Dunning, I., Mourad, S., Larochelle, H., Bellemare, M. G., & Bowling, M. (2020). The Hanabi challenge: A new frontier for AI research. Artificial Intelligence, 280, 19 pages. External link
De Vries, H., Strub, F., Anbil Parthipan, S. C., Pietquin, O., Larochelle, H., & Courville, A. (2017, July). GuessWhat?! Visual Object Discovery through Multi-modal Dialogue [Paper]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, USA. External link
Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C. J., Jodoin, P.-M., & Larochelle, H. (2017). Brain tumor segmentation with Deep Neural Networks. Medical Image Analysis, 35, 18-31. External link
Havaei, M., Dutil, F., Pal, C. J., Larochelle, H., & Jodoin, P.-M. (2015, October). A Convolutional Neural Network Approach to Brain Tumor Segmentation [Paper]. 1st International Workshop on Brain Lesion (BrainLes 2015), Munich, Germany. External link
Maier, O., Menze, B. H., der Gablentz, J. , Häni, L., Heinrich, M. P., Liebrand, M., Winzeck, S., Basit, A., Bentley, P., Chen, L., Christiaens, D., Dutil, F., Egger, K., Feng, C., Glocker, B., Götz, M., Haeck, T., Halme, H.-L., Havaei, M., ... Reyes, M. (2015, October). ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI [Paper]. Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference, Munich, Germany. Published in Medical Image Analysis, 35. External link
Rohrbach, A., Torabi, A., Rohrbach, M., Tandon, N., Pal, C. J., Larochelle, H., Courville, A., & Schiele, B. (2017). Movie description. International Journal of Computer Vision, 123(1), 94-120. Available
Yao, L., Torabi, A., Cho, K., Ballas, N., Pal, C. J., Larochelle, H., & Courville, A. (2015, December). Describing videos by exploiting temporal structure [Paper]. 15th IEEE International Conference on Computer Vision (ICCV 2015), Santiago, Chile. External link