| Cloud programming simplified: A berkeley view on serverless computing E Jonas, J Schleier-Smith, V Sreekanti, CC Tsai, A Khandelwal, Q Pu, ... arXiv preprint arXiv:1902.03383, 2019 | 777 | 2019 |
| Occupy the cloud: Distributed computing for the 99% E Jonas, Q Pu, S Venkataraman, I Stoica, B Recht Proceedings of the 2017 symposium on cloud computing, 445-451, 2017 | 620 | 2017 |
| Could a neuroscientist understand a microprocessor? E Jonas, KP Kording PLoS computational biology 13 (1), e1005268, 2017 | 376 | 2017 |
| DeepLoco: fast 3D localization microscopy using neural networks N Boyd, E Jonas, H Babcock, B Recht BioRxiv, 267096, 2018 | 105 | 2018 |
| Serverless linear algebra V Shankar, K Krauth, K Vodrahalli, Q Pu, B Recht, I Stoica, ... Proceedings of the 11th ACM Symposium on Cloud Computing, 281-295, 2020 | 103 | 2020 |
| Flare prediction using photospheric and coronal image data E Jonas, M Bobra, V Shankar, J Todd Hoeksema, B Recht Solar Physics 293 (3), 48, 2018 | 100 | 2018 |
| Rapid prediction of NMR spectral properties with quantified uncertainty E Jonas, S Kuhn Journal of Cheminformatics 11, 2019 | 97 | 2019 |
| 3D imaging in volumetric scattering media using phase-space measurements HY Liu, E Jonas, L Tian, J Zhong, B Recht, L Waller Optics express 23 (11), 14461-14471, 2015 | 89 | 2015 |
| Towards machine learning on the automata processor T Tracy, Y Fu, I Roy, E Jonas, P Glendenning High Performance Computing: 31st International Conference, ISC High …, 2016 | 74 | 2016 |
| Numpywren: Serverless linear algebra V Shankar, K Krauth, Q Pu, E Jonas, S Venkataraman, I Stoica, B Recht, ... arXiv preprint arXiv:1810.09679, 2018 | 71 | 2018 |
| Prediction of chemical shift in NMR: A review E Jonas, S Kuhn, N Schlörer Magnetic Resonance in Chemistry 60 (11), 1021-1031, 2022 | 66 | 2022 |
| Automatic discovery of cell types and microcircuitry from neural connectomics E Jonas, K Kording Elife 4, e04250, 2015 | 62 | 2015 |
| Crosscat: A fully bayesian nonparametric method for analyzing heterogeneous, high dimensional data V Mansinghka, P Shafto, E Jonas, C Petschulat, M Gasner, ... Journal of Machine Learning Research 17 (138), 1-49, 2016 | 38 | 2016 |
| Stochastic digital circuits for probabilistic inference VK Mansinghka, EM Jonas, JB Tenenbaum Massachussets Institute of Technology, Technical Report MITCSAIL-TR 2069, 2008 | 34 | 2008 |
| Cloud Programming Simplified: A Berkeley View on Serverless Computing. CoRR abs/1902.03383 (2019) E Jonas, J Schleier-Smith, V Sreekanti, C Tsai, A Khandelwal, Q Pu, ... arXiv preprint arXiv:1902.03383, 2019 | 31 | 2019 |
| Deep imitation learning for molecular inverse problems E Jonas Advances in Neural Information Processing Systems, 2019 | 31 | 2019 |
| Rapid approximate subset-based spectra prediction for electron ionization–mass spectrometry RL Zhu, E Jonas Analytical chemistry 95 (5), 2653-2663, 2023 | 30 | 2023 |
| Cloud programming simplified: A berkeley view on serverless computing. arXiv 2019 E Jonas, J Schleier-Smith, V Sreekanti, CC Tsai, A Khandelwal, Q Pu, ... arXiv preprint arXiv:1902.03383, 0 | 30 | |
| Stochastic architectures for probabilistic computation EM Jonas Massachusetts Institute of Technology, 2014 | 28 | 2014 |
| Building fast bayesian computing machines out of intentionally stochastic, digital parts V Mansinghka, E Jonas arXiv preprint arXiv:1402.4914, 2014 | 24 | 2014 |
Konrad Paul KordingNathan Mossell University Professor (PIK), bioengineering & neuroscience, UPenn, CIFAR LMBVerified email at upenn.edu
