| The deep regression bayesian network and its applications: Probabilistic deep learning for computer vision S Nie, M Zheng, Q Ji IEEE Signal Processing Magazine 35 (1), 101-111, 2018 | 79 | 2018 |
| A generative restricted Boltzmann machine based method for high-dimensional motion data modeling S Nie, Z Wang, Q Ji Computer Vision and Image Understanding 136, 14-22, 2015 | 58 | 2015 |
| Advances in learning Bayesian networks of bounded treewidth S Nie, DD Mauá, CP De Campos, Q Ji Advances in neural information processing systems 27, 2014 | 44 | 2014 |
| Capturing global and local dynamics for human action recognition S Nie, Q Ji 2014 22nd International Conference on Pattern Recognition, 1946-1951, 2014 | 33 | 2014 |
| Data-free prior model for upper body pose estimation and tracking J Chen, S Nie, Q Ji IEEE transactions on image processing 22 (12), 4627-4639, 2013 | 29 | 2013 |
| Learning Bayesian Networks with Bounded Tree-width via Guided Search S Nie, CP de Campos, Q Ji The 30th AAAI Conference on Artificial Intelligence, 2016 | 24 | 2016 |
| Differentiating between posed and spontaneous expressions with latent regression Bayesian network Q Gan, S Nie, S Wang, Q Ji Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 22 | 2017 |
| Efficient learning of Bayesian networks with bounded tree-width S Nie, CP de Campos, Q Ji International Journal of Approximate Reasoning 80, 412-427, 2017 | 22 | 2017 |
| Learning Bounded Tree-width Bayesian Networks via Sampling S Nie, CP de Campos, Q Ji Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 13th …, 0 | 22* | |
| Latent regression Bayesian network for data representation S Nie, Y Zhao, Q Ji 2016 23rd International Conference on Pattern Recognition (ICPR), 3494-3499, 2016 | 6 | 2016 |
| Feature learning using Bayesian linear regression model S Nie, Q Ji 2014 22nd International Conference on Pattern Recognition, 1502-1507, 2014 | 6 | 2014 |
| Deep Regression Bayesian Network and Its Applications S Nie, M Zheng, Q Ji arXiv preprint arXiv:1710.04809, 2017 | 4 | 2017 |
| An information theoretic feature selection framework based on integer programming S Nie, T Gao, Q Ji 2016 23rd International Conference on Pattern Recognition (ICPR), 3584-3589, 2016 | 4 | 2016 |
| Asynchronous linear optical sampling for monitoring impairments in multilevel signal modulation format generation H Wen, W Ye, S Nie, X Zheng, H Zhang Asia Communications and Photonics Conference and Exhibition, 83091I, 2011 | 1 | 2011 |
| Efficient learning and inference for probabilistic graphical models S Nie Rensselaer Polytechnic Institute, 2016 | | 2016 |
| Advances in Learning Bayesian Networks of Bounded Treewidth: Supplementary Material S Nie, DD Mauá, CP de Campos, Q Ji | | |
Qiang JiProfessor of Electrical Eng., RPI在 ecse.rpi.edu 的电子邮件经过验证
