| Speed/accuracy trade-offs for modern convolutional object detectors J Huang, V Rathod, C Sun, M Zhu, A Korattikara, A Fathi, I Fischer, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 3640 | 2017 |
| Im2Calories: towards an automated mobile vision food diary A Meyers, N Johnston, V Rathod, A Korattikara, A Gorban, N Silberman, ... Proceedings of the IEEE international conference on computer vision, 1233-1241, 2015 | 580 | 2015 |
| Bayesian posterior sampling via stochastic gradient Fisher scoring S Ahn, A Korattikara, M Welling arXiv preprint arXiv:1206.6380, 2012 | 371 | 2012 |
| Bayesian dark knowledge A Korattikara Balan, V Rathod, KP Murphy, M Welling Advances in neural information processing systems 28, 2015 | 337 | 2015 |
| Austerity in MCMC land: Cutting the Metropolis-Hastings budget A Korattikara, Y Chen, M Welling International conference on machine learning, 181-189, 2014 | 299 | 2014 |
| TF-Agents: A library for reinforcement learning in tensorflow S Guadarrama, A Korattikara, O Ramirez, P Castro, E Holly, S Fishman, ... GitHub repository, 2018 | 201 | 2018 |
| From language to goals: Inverse reinforcement learning for vision-based instruction following J Fu, A Korattikara, S Levine, S Guadarrama arXiv preprint arXiv:1902.07742, 2019 | 150 | 2019 |
| Measuring the reliability of reinforcement learning algorithms SCY Chan, S Fishman, J Canny, A Korattikara, S Guadarrama arXiv preprint arXiv:1912.05663, 2019 | 109 | 2019 |
| Large-scale distributed Bayesian matrix factorization using stochastic gradient MCMC S Ahn, A Korattikara, N Liu, S Rajan, M Welling Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 74 | 2015 |
| others,“ J Huang, V Rathod, C Sun, M Zhu, A Korattikara, A Fathi, I Fischer, ... Speed/accuracy trade-offs for modern convolutional object detectors,” in …, 2017 | 43 | 2017 |
| Statistical optimization of non-negative matrix factorization AK Balan, L Boyles, M Welling, J Kim, H Park Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 16 | 2011 |
| Approximate slice sampling for Bayesian posterior inference C DuBois, A Korattikara, M Welling, P Smyth Artificial Intelligence and Statistics, 185-193, 2014 | 15 | 2014 |
| Statistical tests for optimization efficiency L Boyles, A Korattikara, D Ramanan, M Welling Advances in neural information processing systems 24, 2011 | 10 | 2011 |
| G-RMI object detection A Fathi, A Korattikara, C Sun, I Fischer, J Huang, K Murphy, M Zhu, ... 2nd ImageNet COCO Vis. Recognit. Challenges Joint Workshop, 2016 | 1 | 2016 |
| Sequential tests for large-scale learning A Korattikara, Y Chen, M Welling Neural Computation 28 (1), 45-70, 2015 | 1 | 2015 |
| Approximate Markov Chain Monte Carlo Algorithms for Large Scale Bayesian Inference A Korattikara Balan UC Irvine, 2014 | | 2014 |
| Aji, SM and RJ McEliece (2000, March). The generalized distribu-tive law. IEEE Trans. Info. The-ory 46 (2), 325–343. Alag, S. and A. Agogino (1996). In K Abend, TJ Harley, LN Kanal, D Ackley, G Hinton, T Sejnowski, ... Science 9, 147-169, 0 | | |
| Fast Metropolis-Hastings and Natural Gradient J Canny, D Seita, A Korattikara | | |
Sergio GuadarramaSenior Staff Research Engineer at Google DeepMindVerified email at google.com
