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Thibaut Durand
Thibaut Durand
Machine Learning Researcher @ Borealis AI
Zweryfikowany adres z sfu.ca - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
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
4152017
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
3002019
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
2122016
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
1702019
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
662019
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
432015
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
282020
Exploiting Negative Evidence for Deep Latent Structured Models
T Durand, N Thome, M Cord
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018
282018
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
192021
System and method for a convolutional neural network for multi-label classification with partial annotations
T Durand, N Mehrasa, M Gregory
US Patent 12,020,147, 2024
182024
Point Process Flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
162019
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
152020
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
10*2020
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
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
82020
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
Learning User Representations for Open Vocabulary Image Hashtag Prediction
T Durand
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 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
72014
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