| Sde-net: Equipping deep neural networks with uncertainty estimates L Kong, J Sun, C Zhang ICML 2020, 2020 | 138 | 2020 |
| Adaplanner: Adaptive planning from feedback with language models. H Sun, Y Zhuang, L Kong, B Dai, C Zhang Advances in Neural Information Processing Systems, 2023, 2023 | 102* | 2023 |
| Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data L Kong, H Jiang, Y Zhuang, J Lyu, T Zhao, C Zhang Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 89 | 2020 |
| Autoregressive Diffusion Model for Graph Generation L Kong, J Cui, H Sun, Y Zhuang, BA Prakash, C Zhang ICML 2023, 2023 | 64 | 2023 |
| AcTune: uncertainty-based active self-training for active fine-tuning of pretrained language models Y Yu, L Kong, J Zhang, R Zhang, C Zhang Proceedings of the 2022 conference of the North American chapter of the …, 2022 | 50* | 2022 |
| When in doubt: Neural non-parametric uncertainty quantification for epidemic forecasting H Kamarthi, L Kong, A Rodriguez, C Zhang, BA Prakash Advances in Neural Information Processing Systems 34, 19796-19807, 2021 | 25* | 2021 |
| CAMul: calibrated and accurate multi-view time-series forecasting H Kamarthi, L Kong, A Rodríguez, C Zhang, BA Prakash Proceedings of the ACM Web Conference 2022, 3174-3185, 2022 | 20* | 2022 |
| End-to-end stochastic optimization with energy-based model L Kong, J Cui, Y Zhuang, R Feng, BA Prakash, C Zhang Advances in Neural Information Processing Systems 35, 11341-11354, 2022 | 19 | 2022 |
| When rigidity hurts: Soft consistency regularization for probabilistic hierarchical time series forecasting H Kamarthi, L Kong, A Rodríguez, C Zhang, BA Prakash Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 17* | 2023 |
| Time-mmd: Multi-domain multimodal dataset for time series analysis H Liu, S Xu, Z Zhao, L Kong, H Prabhakar Kamarthi, A Sasanur, ... Advances in Neural Information Processing Systems 37, 77888-77933, 2025 | 14* | 2025 |
| Efficient evolutionary search over chemical space with large language models H Wang, M Skreta, CT Ser, W Gao, L Kong, F Strieth-Kalthoff, C Duan, ... arXiv preprint arXiv:2406.16976, 2024 | 14* | 2024 |
| Dy-Gen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling Y Zhuang, Y Yu, CZ Lingkai Kong, Xiang Chen KDD 2023, 2023 | 12* | 2023 |
| Diffusion models as constrained samplers for optimization with unknown constraints L Kong, Y Du, W Mu, K Neklyudov, V De Bortoli, D Wu, H Wang, A Ferber, ... arXiv preprint arXiv:2402.18012, 2024 | 11* | 2024 |
| Aligning Large Language Models with Representation Editing: A Control Perspective L Kong, H Wang, W Mu, Y Du, Y Zhuang, Y Zhou, Y Song, R Zhang, ... Advances in Neural Information Processing Systems, 2024, 2024 | 11* | 2024 |
| Learning deep hidden nonlinear dynamics from aggregate data Y Wang, B Dai, L Kong, SM Erfani, J Bailey, H Zha UAI 2018, 2018 | 10 | 2018 |
| MUBen: benchmarking the uncertainty of pre-trained models for molecular property prediction Y Li, L Kong, Y Du, Y Yu, Y Zhuang, W Mu, C Zhang TMLR, 2023 | 9* | 2023 |
| Data efficient estimation for quality of transmission through active learning in fiber-wireless integrated network S Yao, CW Hsu, L Kong, Q Zhou, S Shen, R Zhang, SJ Su, Y Alfadhli, ... Journal of Lightwave Technology 39 (18), 5691-5698, 2021 | 6 | 2021 |
| Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning H Liu, H Kamarthi, L Kong, Z Zhao, C Zhang, BA Prakash ICML 2024, 2024 | 5* | 2024 |
| TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidance H Wang, R Zhang, Y Li, L Kong, Y Zhuang, X Chen, C Zhang COLM 2024, 2024 | 4* | 2024 |
| Uncertainty quantification in deep learning L Kong, H Kamarthi, P Chen, BA Prakash, C Zhang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
Chao ZhangAssistant Professor at College of Computing, Georgia TechVahvistettu sähköpostiosoite verkkotunnuksessa gatech.edu