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 | 49256 | 2019 |
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 | 13259 | 2017 |
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 | 1562 | 2019 |
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 | 489 | 2014 |
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 | 343 | 2014 |
Pytorch: An imperative style, high-performance deep learning library, 2019 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703 10, 1912 | 340 | 1912 |
Faster gaze prediction with dense networks and fisher pruning L Theis, I Korshunova, A Tejani, F Huszár arXiv preprint arXiv:1801.05787, 2018 | 240 | 2018 |
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 | 189 | 2016 |
Proceedings of the IEEE conference on computer vision and pattern recognition C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 112 | 2017 |
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 | 70 | 2017 |
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 | 67 | 2019 |
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 | 66 | 2016 |
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 | 56 | 2020 |
Advances in Neural Information Processing Systems 32 ed H A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Wallach et al 8024, 2019 | 55 | 2019 |
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 | 55 | 2016 |
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 | 43 | 2020 |
High-level library to help with training neural networks in pytorch V Fomin, J Anmol, S Desroziers, J Kriss, A Tejani | 37 | 2020 |
PyTorch: An imperative style, high-performance deep learning library.(NeurIPS)(2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... | 24 | 1912 |
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 | 19 | 2021 |
PyTorch: An imperative style, high-performance deep learning library. arXiv [cs. LG] A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 2019 | 18 | 2019 |