Παρακολούθηση
Eugene Belilovsky
Eugene Belilovsky
Assistant Professor, Concordia University and Mila Quebec AI Institute
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα concordia.ca - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Online Continual Learning with Maximally Interfered Retrieval
R Aljundi, L Caccia, E Belilovsky, M Caccia, M Lin, L Charlin, T Tuytelaars
Advances In neural Information Processing Systems (NeurIPS), 2019
467*2019
Scaling the Scattering Transform: Deep Hybrid Networks
E Oyallon, E Belilovsky, S Zagoruyko
International Conference on Computer Vision (ICCV), 5618-5627, 2017
1582017
Greedy Layerwise Learning Can Scale to ImageNet
E Belilovsky, M Eickenberg, E Oyallon
Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019
1382019
Kymatio: Scattering transforms in python
M Andreux, T Angles, G Exarchakisgeo, R Leonardu, G Rochette, L Thiry, ...
The Journal of Machine Learning Research 21 (1), 2256-2261, 2020
1152020
Decoupled greedy learning of cnns
E Belilovsky, M Eickenberg, E Oyallon
Proceedings of the 37th International Conference on Machine Learning (ICML …, 2019
732019
Scattering networks for hybrid representation learning
E Oyallon, S Zagoruyko, G Huang, N Komodakis, S Lacoste-Julien, ...
IEEE transactions on pattern analysis and machine intelligence 41 (9), 2208-2221, 2018
732018
A Test of Relative Similarity for Model Selection in Generative Models
E Belilovsky, W Bounliphone, MB Blaschko, I Antonoglou, A Gretton
International Conference on Learning Representations (ICLR), 2016
69*2016
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity
E Belilovsky, G Varoquaux, MB Blaschko
Advances In neural Information Processing Systems (NIPS), 2016
592016
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
L Caccia, R Aljundi, N Asadi, T Tuytelaars, J Pineau, E Belilovsky
International Conference on Learning Representations (ICLR), 2022
57*2022
Online Learned Continual Compression with Adaptive Quantization Modules
L Caccia, E Belilovsky, M Caccia, J Pineau
International Conference on Machine Learning (ICML), 2020
56*2020
Blindfold Baselines for Embodied QA
A Anand, E Belilovsky, K Kastner, H Larochelle, A Courville
NIPS VIGIL Workshop arXiv preprint arXiv:1811.05013, 2018
482018
CLIP-Mesh: Generating textured meshes from text using pretrained image-text models
N Mohammad Khalid, T Xie, E Belilovsky, T Popa
SIGGRAPH Asia 2022 Conference Papers, 1-8, 2022
46*2022
Compressing the Input for CNNs with the First-Order Scattering Transform
E Oyallon, E Belilovsky, S Zagoruyko, M Valko
European Conference on Computer Vision (ECCV), 2018
312018
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning
MR Davari, N Asadi, S Mudur, R Aljundi, E Belilovsky
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
292022
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
B Knyazev, H de Vries, C Cangea, GW Taylor, A Courville, E Belilovsky
British Machine Vision Conference (BMVC), 2020
272020
Learning to Discover Sparse Graphical Models
E Belilovsky, K Kastner, G Varoquaux, MB Blaschko
International Conference on Machine Learning (ICML), 2017
272017
Graph density-aware losses for novel compositions in scene graph generation
EB Knyazev, Boris, Harm de Vries, Catalina Cangea, Graham W Taylor, Aaron ...
arXiv preprint arXiv:2005.08230 2 (3), 2020
26*2020
Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm
E Belilovsky, K Gkirtzou, M Misyrlis, AB Konova, J Honorio, N Alia-Klein, ...
Computerized Medical Imaging and Graphics 46, 40-46, 2015
23*2015
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
M Michalkiewicz, S Parisot, S Tsogkas, M Baktashmotlagh, A Eriksson, ...
ECCV 2020 arXiv preprint arXiv:2004.06302, 2020
192020
Joint Embeddings of Scene Graphs and Images
E Belilovsky, M Blaschko, JR Kiros, R Urtasun, R Zemel
International Conference on Learning Representations (ICLR) Workshop Track, 2017
182017
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