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Thibaut Durand
Thibaut Durand
Machine Learning Researcher @ Borealis AI
Bestätigte E-Mail-Adresse bei sfu.ca - Startseite
Titel
Zitiert von
Zitiert von
Jahr
WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation
T Durand, T Mordan, N Thome, M Cord
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
3482017
WELDON: Weakly supervised learning of deep convolutional neural networks
T Durand, N Thome, M Cord
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
1852016
Learning a deep convnet for multi-label classification with partial labels
T Durand, N Mehrasa, G Mori
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1542019
LayoutVAE: Stochastic scene layout generation from a label set
AA Jyothi, T Durand, J He, L Sigal, G Mori
Proceedings of the IEEE International Conference on Computer Vision, 9895-9904, 2019
782019
A variational auto-encoder model for stochastic point processes
N Mehrasa, AA Jyothi, T Durand, J He, L Sigal, G Mori
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
472019
MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking
T Durand, N Thome, M Cord
Proceedings of the IEEE International Conference on Computer Vision, 2713-2721, 2015
402015
Exploiting Negative Evidence for Deep Latent Structured Models
T Durand, N Thome, M Cord
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
242018
Higher runoff and soil detachment in rubber tree plantations compared to annual cultivation is mitigated by ground cover in steep mountainous Thailand
M Neyret, H Robain, A De Rouw, JL Janeau, T Durand, J Kaewthip, ...
Catena 189, 104472, 2020
132020
Point Process Flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
102019
Image classification using object detectors
T Durand, N Thome, M Cord, S Avila
ICIP 2013: IEEE International Conference on Image Processing, 4340-4344, 2013
102013
Incremental Learning of Latent Structural SVM for Weakly Supervised Image Classification
T Durand, N Thome, M Cord, D Picard
IEEE International Conference on Image Processing 2014, 2014
92014
SyMIL: MinMax Latent SVM for Weakly Labeled Data
T Durand, N Thome, M Cord
IEEE transactions on neural networks and learning systems 29 (12), 6099-6112, 2018
82018
Weakly supervised learning for visual recognition
T Durand
Université Pierre et Marie Curie, 2017
82017
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Y Gong, H Hajimirsadeghi, J He, T Durand, G Mori
International Conference on Artificial Intelligence and Statistics, 2377-2385, 2021
72021
Variational Selective Autoencoder
Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori
Symposium on Advances in Approximate Bayesian Inference, 1-17, 2020
72020
Semantic Pooling for Image Categorization using Multiple Kernel Learning
T Durand, D Picard, N Thome, M Cord
IEEE International Conference on Image Processing 2014, 2014
62014
Learning User Representations for Open Vocabulary Image Hashtag Prediction
T Durand
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
52020
System and method for a convolutional neural network for multi-label classification with partial annotations
T Durand, N Mehrasa, M Gregory
US Patent App. 16/685,478, 2020
32020
SYSTEM AND METHOD FOR MACHINE LEARNING ARCHITECTURE FOR PARTIALLY-OBSERVED MULTIMODAL DATA
Y Gong, J HE, T Durand, M Nawhal, Y Cao, G Mori, SH Hajimirsadeghi
US Patent App. 16/882,074, 2020
22020
System and method for generative model for stochastic point processes
N Mehrasa, AA Jyothi, T Durand, J He, M Gregory, M Ahmed, M Brubaker
US Patent App. 16/685,327, 2020
22020
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