Publications
Probing the Decision Boundaries of In-context Learning in LLMs
Siyan Zhao, Tung Nguyen, Aditya Grover
Conference on Neural Information Processing Systems (NeurIPS 2024)
[paper] [code]
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine
Conference on Neural Information Processing Systems (NeurIPS 2024)
[paper] [code]
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, Aditya Grover
Conference on Neural Information Processing Systems (NeurIPS 2024)
Best Paper Award, Tackling Climate Change with Machine Learning Workshop, ICLR 2024
[paper] [code] [slide]
ExPT: Synthetic Pretraining for Few-Shot Experimental Design
Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
Conference on Neural Information Processing Systems (NeurIPS 2023)
[paper] [code] [slide]
ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
Tung Nguyen, Jason Kyle Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
Conference on Neural Information Processing Systems (NeurIPS 2023)
[paper] [code] [slide]
ClimaX: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta*, Aditya Grover*
The 40th International Conference on Machine Learning (ICML 2023)
Best Paper at ICML Workshop on Synergy of Scientific and Machine Learning Modeling, Spotlight Oral at ICLR Workshop on AI and Climate Change
[paper] [code] [blog] [slide] [talk]
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
Tung Nguyen, Aditya Grover
The 39th International Conference on Machine Learning (ICML 2022)
[paper] [code] [slide] [talk]
Temporal Predictive Coding for Model-based Planning in Latent Space
Tung Nguyen*, Rui Shu*, Tuan Pham*, Hung Bui, Stefano Ermon
The 38th International Conference on Machine Learning (ICML 2021)
[paper] [code] [slide] [talk]
Predictive Coding for Locally-Linear Control
Rui Shu*, Tung Nguyen*, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui
The 37th International Conference on Machine Learning (ICML 2020)
[paper] [code] [blog] [slide] [talk]
Infinite Dropout for training Bayesian models from data streams
Van-Son Nguyen, Tung Nguyen, Linh Ngo Van, Khoat Than
IEEE International Conference on Big Data (Big Data 2019)
[paper]
* denotes equal contribution