Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022 | 258* | 2022 |
Ensemble forecasts of coronavirus disease 2019 (COVID-19) in the US EL Ray, N Wattanachit, J Niemi, AH Kanji, K House, EY Cramer, J Bracher, ... MedRXiv, 2020.08. 19.20177493, 2020 | 204 | 2020 |
A finite-time analysis of two time-scale actor-critic methods YF Wu, W Zhang, P Xu, Q Gu Advances in Neural Information Processing Systems 33, 17617-17628, 2020 | 128 | 2020 |
Epidemic model guided machine learning for COVID-19 forecasts in the United States D Zou, L Wang, P Xu, J Chen, W Zhang, Q Gu MedRxiv, 2020.05. 24.20111989, 2020 | 116 | 2020 |
Neural thompson sampling W Zhang, D Zhou, L Li, Q Gu arXiv preprint arXiv:2010.00827, 2020 | 96 | 2020 |
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave J Bracher, D Wolffram, J Deuschel, K Görgen, JL Ketterer, A Ullrich, ... Nature communications 12 (1), 5173, 2021 | 62 | 2021 |
Multiple models for outbreak decision support in the face of uncertainty K Shea, RK Borchering, WJM Probert, E Howerton, TL Bogich, SL Li, ... Proceedings of the National Academy of Sciences 120 (18), e2207537120, 2023 | 44* | 2023 |
Reward-free model-based reinforcement learning with linear function approximation W Zhang, D Zhou, Q Gu Advances in Neural Information Processing Systems 34, 1582-1593, 2021 | 31 | 2021 |
A simulation system and speed guidance algorithms for intersection traffic control using connected vehicle technology S Liu, W Zhang, X Wu, S Feng, X Pei, D Yao Tsinghua Science and Technology 24 (2), 160-170, 2018 | 31 | 2018 |
Electrochemical mechanistic analysis from cyclic voltammograms based on deep learning BB Hoar, W Zhang, S Xu, R Deeba, C Costentin, Q Gu, C Liu ACS Measurement Science Au 2 (6), 595-604, 2022 | 21 | 2022 |
Provably efficient representation selection in low-rank Markov decision processes: from online to offline RL W Zhang, J He, D Zhou, Q Gu, A Zhang Uncertainty in Artificial Intelligence, 2488-2497, 2023 | 17* | 2023 |
Rephrase and respond: Let large language models ask better questions for themselves Y Deng, W Zhang, Z Chen, Q Gu arXiv preprint arXiv:2311.04205, 2023 | 15 | 2023 |
Learning neural contextual bandits through perturbed rewards Y Jia, W Zhang, D Zhou, Q Gu, H Wang arXiv preprint arXiv:2201.09910, 2022 | 8 | 2022 |
On the interplay between misspecification and sub-optimality gap in linear contextual bandits W Zhang, J He, Z Fan, Q Gu International Conference on Machine Learning, 41111-41132, 2023 | 6* | 2023 |
Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance L Zhao, Y Deng, W Zhang, Q Gu arXiv preprint arXiv:2402.08680, 2024 | 5 | 2024 |
MoleculeGPT: Instruction Following Large Language Models for Molecular Property Prediction W Zhang, X Wang, W Nie, J Eaton, B Rees, Q Gu NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development, 2023 | 3 | 2023 |
Diffmol: 3d structured molecule generation with discrete denoising diffusion probabilistic models W Zhang, X Wang, J Smith, J Eaton, B Rees, Q Gu ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023 | 2 | 2023 |
Optimal horizon-free reward-free exploration for linear mixture mdps J Zhang, W Zhang, Q Gu International Conference on Machine Learning, 41902-41930, 2023 | 2 | 2023 |
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs K Ji, Q Zhao, J He, W Zhang, Q Gu arXiv preprint arXiv:2305.08359, 2023 | 2 | 2023 |
Challenges of COVID-19 Case Forecasting in the US, 2020–2021 VK Lopez, EY Cramer, R Pagano, JM Drake, EB O’Dea, M Adee, T Ayer, ... PLoS computational biology 20 (5), e1011200, 2024 | 1 | 2024 |