| Sparse deep belief net model for visual area V2 H Lee, C Ekanadham, A Ng Advances in neural information processing systems 20, 2007 | 1355 | 2007 |
| Recovery of sparse translation-invariant signals with continuous basis pursuit C Ekanadham, D Tranchina, EP Simoncelli IEEE transactions on signal processing 59 (10), 4735-4744, 2011 | 288 | 2011 |
| Back to the basics: Bayesian extensions of IRT outperform neural networks for proficiency estimation KH Wilson, Y Karklin, B Han, C Ekanadham arXiv preprint arXiv:1604.02336, 2016 | 151 | 2016 |
| A unified framework and method for automatic neural spike identification C Ekanadham, D Tranchina, EP Simoncelli Journal of neuroscience methods 222, 47-55, 2014 | 113 | 2014 |
| Towards perceptually optimized end-to-end adaptive video streaming CG Bampis, Z Li, I Katsavounidis, TY Huang, C Ekanadham, AC Bovik arXiv preprint arXiv:1808.03898, 2018 | 94 | 2018 |
| Estimating student proficiency: Deep learning is not the panacea KH Wilson, X Xiong, M Khajah, RV Lindsey, S Zhao, Y Karklin, ... In Neural information processing systems, workshop on machine learning for …, 2016 | 60 | 2016 |
| T-skirt: Online estimation of student proficiency in an adaptive learning system C Ekanadham, Y Karklin arXiv preprint arXiv:1702.04282, 2017 | 56 | 2017 |
| A blind sparse deconvolution method for neural spike identification C Ekanadham, D Tranchina, E Simoncelli Advances in neural information processing systems 24, 2011 | 42 | 2011 |
| Towards perceptually optimized adaptive video streaming-a realistic quality of experience database CG Bampis, Z Li, I Katsavounidis, TY Huang, C Ekanadham, AC Bovik IEEE Transactions on Image Processing 30, 5182-5197, 2021 | 34 | 2021 |
| Hindsight: Evaluate video bitrate adaptation at scale TY Huang, C Ekanadham, AJ Berglund, Z Li Proceedings of the 10th ACM Multimedia Systems Conference, 86-97, 2019 | 28 | 2019 |
| Sparse decomposition of transformation-invariant signals with continuous basis pursuit C Ekanadham, D Tranchina, EP Simoncelli 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 19 | 2011 |
| Systems and methods for generating applications that are automatically optimized for network performance JM Huerta, DM Lubensky, CJK Ekanadham US Patent 7,437,707, 2008 | 17 | 2008 |
| Hierarchical spike coding of sound Y Karklin, C Ekanadham, E Simoncelli Advances in neural information processing systems 25, 2012 | 14 | 2012 |
| Supporting content decision makers with machine learning M Dye, C Ekanadham, A Saluja, A Rastogi Netflix tech blog, 2020 | 12 | 2020 |
| Neural spike identification with continuous basis pursuit C Ekanadham, D Tranchina, EP Simoncelli Computational and Systems Neuroscience (CoSyNe), Salt Lake City, Utah, 2011 | 10 | 2011 |
| Using machine learning to improve streaming quality at netflix C Ekanadham Netflix Tech Blog, 2018 | 9 | 2018 |
| Towards perceptually optimized end-to-end adaptive video streaming. arxiv 2018 CG Bampis, Z Li, I Katsavounidis, TY Huang, C Ekanadham, AC Bovik arXiv preprint arXiv:1808.03898, 2018 | 8 | 2018 |
| Continuous basis pursuit and its applications C Ekanadham New York University, 2012 | 6 | 2012 |
| Sparse deep belief net models for visual area V2. Undergraduate honors thesis C Ekanadham Stanford University 55, 147, 2007 | 4 | 2007 |
| Subjective analysis of an end-to-end streaming system CG Bampis, Z Li, I Katsavounidis, C Ekanadham, AC Bovik Electronic Imaging 31, 1-8, 2019 | 1 | 2019 |
