| 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, 8026-8037, 2019 | 7458 | 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 | 6077 | 2017 |
| 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 | 368 | 2014 |
| Latent-class hough forests for 3d object detection and pose estimation A Tejani, D Tang, R Kouskouridas, TK Kim European Conference on Computer Vision, 462-477, 2014 | 251 | 2014 |
| 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 | 204 | 2019 |
| Faster gaze prediction with dense networks and fisher pruning L Theis, I Korshunova, A Tejani, F Huszár arXiv preprint arXiv:1801.05787, 2018 | 105 | 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 | 91 | 2016 |
| 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 | 40 | 2017 |
| 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 | 29 | 2016 |
| 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 | 16 | 2019 |
| Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline L Belli, SI Ktena, A Tejani, A Lung-Yut-Fon, F Portman, X Zhu, Y Xie, ... | 10 | 2020 |
| Latent-class hough forests for 6 dof object pose estimation R Kouskouridas, A Tejani, A Doumanoglou, D Tang, TK Kim arXiv preprint arXiv:1602.01464, 2016 | 10 | 2016 |
| Estimator training method and pose estimating method using depth image JJ Han, D Tang, TK Kim, SJ Han, BI Yoo, CK Choi, A Tejani, HJ Chang US Patent 9,449,392, 2016 | 5 | 2016 |
| Estimator training method and pose estimating method using depth image JJ Han, D Tang, TK Kim, SJ Han, BI Yoo, CK Choi, A Tejani, HJ Chang US Patent 9,449,392, 2016 | 5 | 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 Fourteenth ACM Conference on Recommender Systems, 456-461, 2020 | 4 | 2020 |
| Estimator training method and pose estimating method using depth image JJ Han, D Tang, TK Kim, SJ Han, BI Yoo, CK Choi, A Tejani, HJ Chang US Patent 9,311,713, 2016 | 4 | 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, ... Fourteenth ACM Conference on Recommender Systems, 521-526, 2020 | 3 | 2020 |
| RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter’s Home Timeline VW Anelli, A Delić, G Sottocornola, J Smith, N Andrade, L Belli, ... Fourteenth ACM Conference on Recommender Systems, 623-627, 2020 | 1 | 2020 |
| Privacy-Aware Recommender Systems Challenge on Twitter's Home Timeline L Belli, SI Ktena, A Tejani, A Lung-Yut-Fon, F Portman, X Zhu, Y Xie, ... arXiv preprint arXiv:2004.13715, 2020 | 1 | 2020 |
| Lucas Theis L THEIS, I Korshunova, A Tejani US Patent App 15, 707,294, 2018 | | 2018 |
Wenzhe Shi（施闻哲）Recommender Systems Research, Twitter Inc, Cortex Applied ResearchVerified email at twitter.com
