| Neural architecture search with bayesian optimisation and optimal transport K Kandasamy, W Neiswanger, J Schneider, B Poczos, E Xing Proceedings of the 32nd International Conference on Neural Information …, 2018 | 725 | 2018 |
| Asymptotically Exact, Embarrassingly Parallel MCMC W Neiswanger, C Wang, E Xing | 428 | 2014 |
| Bananas: Bayesian optimization with neural architectures for neural architecture search C White, W Neiswanger, Y Savani Proceedings of the AAAI Conference on Artificial Intelligence 35, 2021 | 373 | 2021 |
| Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly K Kandasamy, KR Vysyaraju, W Neiswanger, B Paria, CR Collins, ... Journal of Machine Learning Research 21 (81), 1-27, 2020 | 229 | 2020 |
| Methods for comparing uncertainty quantifications for material property predictions K Tran, W Neiswanger, J Yoon, Q Zhang, E Xing, ZW Ulissi Machine Learning: Science and Technology 1 (2), 025006, 2020 | 205 | 2020 |
| Pollux: Co-adaptive cluster scheduling for goodput-optimized deep learning A Qiao, SK Choe, SJ Subramanya, W Neiswanger, Q Ho, H Zhang, ... 15th {USENIX} Symposium on Operating Systems Design and Implementation …, 2021 | 181 | 2021 |
| Chembo: Bayesian optimization of small organic molecules with synthesizable recommendations K Korovina, S Xu, K Kandasamy, W Neiswanger, B Poczos, J Schneider, ... International Conference on Artificial Intelligence and Statistics, 3393-3403, 2020 | 142 | 2020 |
| Beyond pinball loss: Quantile methods for calibrated uncertainty quantification Y Chung, W Neiswanger, I Char, J Schneider Proceedings of the 35th International Conference on Neural Information …, 2021 | 101 | 2021 |
| Uncertainty toolbox: an open-source library for assessing, visualizing, and improving uncertainty quantification Y Chung, I Char, H Guo, J Schneider, W Neiswanger arXiv preprint arXiv:2109.10254, 2021 | 95 | 2021 |
| Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling B Boecking, W Neiswanger, E Xing, A Dubrawski International Conference on Learning Representations (ICLR), 2021 | 90 | 2021 |
| A study on encodings for neural architecture search C White, W Neiswanger, S Nolen, Y Savani Advances in Neural Information Processing Systems 33, 2020 | 82 | 2020 |
| Synthetic benchmarks for scientific research in explainable machine learning Y Liu, S Khandagale, C White, W Neiswanger arXiv preprint arXiv:2106.12543, 2021 | 75 | 2021 |
| Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis Y Xiao, PP Liang, U Bhatt, W Neiswanger, R Salakhutdinov, LP Morency Findings of the Association for Computational Linguistics: EMNLP 2022, 2022 | 71 | 2022 |
| Offline contextual bayesian optimization I Char, Y Chung, W Neiswanger, K Kandasamy, AO Nelson, M Boyer, ... Advances in Neural Information Processing Systems 32, 2019 | 59* | 2019 |
| Parallel and distributed block-coordinate frank-wolfe algorithms YX Wang, V Sadhanala, W Dai, W Neiswanger, S Sra, E Xing International Conference on Machine Learning, 1548-1557, 2016 | 53 | 2016 |
| Fast distribution to real regression J Oliva, W Neiswanger, B Póczos, J Schneider, E Xing Artificial Intelligence and Statistics, 706-714, 2014 | 52 | 2014 |
| Llm360: Towards fully transparent open-source llms Z Liu, A Qiao, W Neiswanger, H Wang, B Tan, T Tao, J Li, Y Wang, S Sun, ... arXiv preprint arXiv:2312.06550, 2023 | 46 | 2023 |
| The dependent Dirichlet process mixture of objects for detection-free tracking and object modeling W Neiswanger, F Wood, E P Xing International Conference on Artificial Intelligence and Statistics (AISTATS …, 2014 | 46* | 2014 |
| Durable interactions of T cells with T cell receptor stimuli in the absence of a stable immunological synapse V Mayya, E Judokusumo, EA Shah, CG Peel, W Neiswanger, D Depoil, ... Cell reports 22 (2), 340-349, 2018 | 45 | 2018 |
| Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information W Neiswanger, KA Wang, S Ermon International Conference on Machine Learning, 2021 | 39 | 2021 |
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UEmail verificata su cs.cmu.edu
