| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1352 | 2022 |
| The AI index 2021 annual report D Zhang, S Mishra, E Brynjolfsson, J Etchemendy, D Ganguli, B Grosz, ... arXiv preprint arXiv:2103.06312, 2021 | 568 | 2021 |
| HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models S Zhou, M Gordon, R Krishna, A Narcomey, FF Li, MS Bernstein Advances in Neural information Processing Systems (NeurIPS), 3444-3456, 2019 | 173 | 2019 |
| Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J Irvin, S Zhou, G McNicol, F Lu, V Liu, E Fluet-Chouinard, Z Ouyang, ... Agricultural and Forest Meteorology 308, 108528, 2021 | 80 | 2021 |
| Countdown Regression: Sharp and Calibrated Survival Predictions A Avati, T Duan, S Zhou, K Jung, NH Shah, A Ng Proceedings of the 35th UAI Conference on Uncertainty in Artificial Intelligence, 2019 | 72 | 2019 |
| In Search of the Dream Team: Temporally Constrained Multi-Armed Bandits for Identifying Effective Team Structures S Zhou, M Valentine, MS Bernstein Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems …, 2018 | 58 | 2018 |
| Forestnet: Classifying drivers of deforestation in indonesia using deep learning on satellite imagery J Irvin, H Sheng, N Ramachandran, S Johnson-Yu, S Zhou, K Story, ... arXiv preprint arXiv:2011.05479, 2020 | 53 | 2020 |
| Boomerang: Rebounding the consequences of reputation feedback on crowdsourcing platforms SNS Gaikwad, D Morina, A Ginzberg, C Mullings, S Goyal, D Gamage, ... Proceedings of the 29th UIST Annual Symposium on User Interface Software and …, 2016 | 42 | 2016 |
| Data augmentation with Mobius transformations S Zhou, J Zhang, H Jiang, T Lundh, AY Ng https://iopscience.iop.org/article/10.1088/2632-2153/abd615, 2020 | 32 | 2020 |
| CheXphoto: 10,000+ photos and transformations of chest X-rays for benchmarking deep learning robustness NA Phillips, P Rajpurkar, M Sabini, R Krishnan, S Zhou, A Pareek, ... Machine Learning for Health, 318-327, 2020 | 32 | 2020 |
| Evaluating the Disentanglement of Deep Generative Models through Manifold Topology S Zhou, E Zelikman, F Lu, AY Ng, G Carlsson, S Ermon ICLR 2021, 2020 | 31 | 2020 |
| DeepWind: Weakly Supervised Localization of Wind Turbines in Satellite Imagery S Zhou, J Irvin, Z Wang, E Zhang, J Aljubran, W Deadrick, R Rajagopal, ... Neural information Processing Systems (NeurIPS) Workshop on Tackling Climate …, 2019 | 29* | 2019 |
| Deep learning assistance for the histopathologic diagnosis of Helicobacter pylori S Zhou, H Marklund, O Blaha, M Desai, B Martin, D Bingham, GJ Berry, ... Intelligence-Based Medicine 1, 100004, 2020 | 26 | 2020 |
| Short-term solar irradiance forecasting using calibrated probabilistic models E Zelikman, S Zhou, J Irvin, C Raterink, H Sheng, A Avati, J Kelly, ... arXiv preprint arXiv:2010.04715, 2020 | 23 | 2020 |
| The daemo crowdsourcing marketplace SNS Gaikwad, ME Whiting, D Gamage, CA Mullings, D Majeti, S Goyal, ... Companion of the 2017 ACM conference on computer supported cooperative work …, 2017 | 18 | 2017 |
| Ingenium: Engaging Novice Students with Latin Grammar S Zhou, IJ Livingston, M Schiefsky, SM Shieber, KZ Gajos Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems …, 2016 | 17 | 2016 |
| CRUDE: calibrating regression uncertainty distributions empirically E Zelikman, C Healy, S Zhou, A Avati arXiv preprint arXiv:2005.12496, 2020 | 16 | 2020 |
| Prototype tasks: improving crowdsourcing results through rapid, iterative task design S Gaikwad, N Chhibber, V Sehgal, A Ballav, C Mullings, A Nasser, ... HCOMP 2017, 2017 | 10 | 2017 |
| Banishing LLM hallucinations requires rethinking generalization J Li, S Consul, E Zhou, J Wong, N Farooqui, Y Ye, N Manohar, Z Wei, ... arXiv preprint arXiv:2406.17642, 2024 | 8 | 2024 |
| Approximating Human Judgment of Generated Image Quality YA Kolchinski, S Zhou, S Zhao, M Gordon, S Ermon Neural information Processing Systems (NeurIPS) Workshop on Shared Visual …, 2019 | 8 | 2019 |
Andrew NgStanford UniversityVerifisert e-postadresse på cs.stanford.edu