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Alykhan Tejani
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Pytorch: An imperative style, high-performance deep learning library
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Advances in neural information processing systems 32, 2019
401722019
Photo-realistic single image super-resolution using a generative adversarial network
C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
124022017
Advances in neural information processing systems 32
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Curran Associates, Inc, 8024-8035, 2019
10172019
Pytorch: An imperative style, high-performance deep learning library
B Steiner, Z DeVito, S Chintala, S Gross, A Paske, F Massa, A Lerer, ...
6662019
Latent regression forest: Structured estimation of 3d articulated hand posture
D Tang, H Jin Chang, A Tejani, TK Kim
Proceedings of the IEEE conference on computer vision and pattern …, 2014
4672014
Latent-class hough forests for 3d object detection and pose estimation
A Tejani, D Tang, R Kouskouridas, TK Kim
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
3292014
Faster gaze prediction with dense networks and fisher pruning
L Theis, I Korshunova, A Tejani, F Huszár
arXiv preprint arXiv:1801.05787, 2018
2122018
Is the deconvolution layer the same as a convolutional layer?
W Shi, J Caballero, L Theis, F Huszar, A Aitken, C Ledig, Z Wang
arXiv preprint arXiv:1609.07009, 2016
1762016
Pytorch: An imperative style, high-performance deep learning library. arXiv 2019
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
arXiv preprint arXiv:1912.01703, 1912
1731912
PyTorch: An Imperative Style
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
High-Performance Deep Learning Library 12, 1912
1201912
Photo-realistic single image super-resolution using a generative adversarial network. arXiv 2016
C Ledig, L Theis, F Huszar, J Caballero, A Cunningham, A Acosta, ...
arXiv preprint arXiv:1609.04802, 2016
662016
Latent-class hough forests for 6 DoF object pose estimation
A Tejani, R Kouskouridas, A Doumanoglou, D Tang, TK Kim
IEEE transactions on pattern analysis and machine intelligence 40 (1), 119-132, 2017
652017
Addressing delayed feedback for continuous training with neural networks in CTR prediction
SI Ktena, A Tejani, L Theis, PK Myana, D Dilipkumar, F Huszár, S Yoo, ...
Proceedings of the 13th ACM conference on recommender systems, 187-195, 2019
602019
Advances in Neural Information Processing Systems 32, Curran Associates
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Inc., New York, 8024, 2019
562019
Latent regression forest: structured estimation of 3d hand poses
D Tang, HJ Chang, A Tejani, TK Kim
IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (7), 1374-1387, 2016
532016
Deep bayesian bandits: Exploring in online personalized recommendations
D Guo, SI Ktena, PK Myana, F Huszar, W Shi, A Tejani, M Kneier, S Das
Proceedings of the 14th ACM Conference on Recommender Systems, 456-461, 2020
372020
Model size reduction using frequency based double hashing for recommender systems
C Zhang, Y Liu, Y Xie, SI Ktena, A Tejani, A Gupta, PK Myana, ...
Proceedings of the 14th ACM Conference on Recommender Systems, 521-526, 2020
342020
High-level library to help with training neural networks in pytorch
V Fomin, J Anmol, S Desroziers, J Kriss, A Tejani
312020
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter’s Home Timeline
VW Anelli, S Kalloori, B Ferwerda, L Belli, A Tejani, F Portman, ...
Proceedings of the 15th ACM Conference on Recommender Systems, 819-824, 2021
152021
RecSys 2020 challenge workshop: engagement prediction on Twitter’s home timeline
VW Anelli, A Delić, G Sottocornola, J Smith, N Andrade, L Belli, ...
Proceedings of the 14th ACM Conference on Recommender Systems, 623-627, 2020
152020
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