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Priya Goyal
Priya Goyal
Staff Research Engineer, Google Deepmind
Dirección de correo verificada de google.com - Página principal
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Citado por
Citado por
Año
Focal Loss for Dense Object Detection
TY Lin, P Goyal, R Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002, 2017
279492017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ...
https://arxiv.org/abs/1706.02677, 2017
37082017
Unsupervised learning of visual features by contrasting cluster assignments
M Caron, I Misra, J Mairal, P Goyal, P Bojanowski, A Joulin
Advances in neural information processing systems 33, 9912-9924, 2020
32332020
Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions
N Vasilache, O Zinenko, T Theodoridis, P Goyal, Z DeVito, WS Moses, ...
arXiv preprint arXiv:1802.04730, 2018
4652018
Scaling and Benchmarking Self-Supervised Visual Representation Learning
P Goyal, D Mahajan, A Gupta, I Misra
https://arxiv.org/abs/1905.01235, 2019
4232019
Self-supervised pretraining of visual features in the wild
P Goyal, M Caron, B Lefaudeux, M Xu, P Wang, V Pai, M Singh, ...
arXiv preprint arXiv:2103.01988, 2021
2412021
Focal loss for dense object detection. arXiv 2017
TY Lin, P Goyal, R Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002, 2002
1302002
Accurate, large minibatch sgd: Training imagenet in 1 hour. arXiv 2017
P Goyal, P Dollár, R Girshick, P Noordhuis, L Wesolowski, A Kyrola, ...
arXiv preprint arXiv:1706.02677, 2019
932019
Focal loss for dense object detection. arXiv
TY Lin, P Goyal, R Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002, 2017
932017
Vision models are more robust and fair when pretrained on uncurated images without supervision
P Goyal, Q Duval, I Seessel, M Caron, I Misra, L Sagun, A Joulin, ...
arXiv preprint arXiv:2202.08360, 2022
842022
VISSL
P Goyal, B Lefaudeux, M Singh, J Reizenstein, V Reis, M Xu, M Leavitt, ...
702021
Piotr Doll ar. Focal loss for dense object detection
TY Lin, P Goyal, R Girshick, K He
Proceedings of the IEEE International Conference on Computer Vision (ICCV …, 2017
692017
The next 700 accelerated layers: From mathematical expressions of network computation graphs to accelerated gpu kernels, automatically
N Vasilache, O Zinenko, T Theodoridis, P Goyal, Z Devito, WS Moses, ...
ACM Transactions on Architecture and Code Optimization (TACO) 16 (4), 1-26, 2019
632019
Focal loss for dense object detection. CoRR abs/1708.02002 (2017)
T Lin, P Goyal, RB Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002, 2017
582017
A self-supervised descriptor for image copy detection
E Pizzi, SD Roy, SN Ravindra, P Goyal, M Douze
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
282022
P. Doll ar. 2017. Focal loss for dense object detection
TY Lin, P Goyal, R Girshick, K He
Proceedings of the IEEE International Conference on Computer Vision. IEEE …, 2017
24*2017
Fairness indicators for systematic assessments of visual feature extractors
P Goyal, AR Soriano, C Hazirbas, L Sagun, N Usunier
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
172022
Focal loss for dense object detection. arXiv e-prints
TY Lin, P Goyal, R Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002 2 (5), 2017
162017
GitHub repository
TLI Lin, P Goyal, R Girshick, K He, P Dollar, RN TF
GenQSGD, 2018
152018
Focal loss for dense object detection. CoRR abs/1708.02002
T Lin, P Goyal, RB Girshick, K He, P Dollár
arXiv preprint arXiv:1708.02002, 2017
132017
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Artículos 1–20