1 code implementation • 11 Mar 2024 • Junhong Shen, Tanya Marwah, Ameet Talwalkar
We introduce UPS (Unified PDE Solver), an effective and data-efficient approach to solve diverse spatiotemporal PDEs defined over various domains, dimensions, and resolutions.
1 code implementation • 6 Feb 2024 • Junhong Shen, Neil Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolo Fusi
Large Language Models (LLMs) have demonstrated remarkable proficiency in understanding and generating natural language.
1 code implementation • 11 Feb 2023 • Junhong Shen, Liam Li, Lucio M. Dery, Corey Staten, Mikhail Khodak, Graham Neubig, Ameet Talwalkar
Fine-tuning large-scale pretrained models has led to tremendous progress in well-studied modalities such as vision and NLP.
1 code implementation • 15 Apr 2022 • Junhong Shen, Mikhail Khodak, Ameet Talwalkar
While neural architecture search (NAS) has enabled automated machine learning (AutoML) for well-researched areas, its application to tasks beyond computer vision is still under-explored.
1 code implementation • 12 Oct 2021 • Renbo Tu, Nicholas Roberts, Mikhail Khodak, Junhong Shen, Frederic Sala, Ameet Talwalkar
This makes the performance of NAS approaches in more diverse areas poorly understood.
no code implementations • 9 Oct 2021 • Junhong Shen, Lin F. Yang
To mitigate these issues, we propose a theoretically principled nearest neighbor (NN) function approximator that can improve the value networks in deep RL methods.
1 code implementation • NeurIPS 2021 • Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
Recently, the benefits of integrating this cooperative pedagogy into machine concept learning in discrete spaces have been proved by multiple works.
1 code implementation • 21 Jan 2020 • Luyao Yuan, Zipeng Fu, Jingyue Shen, Lu Xu, Junhong Shen, Song-Chun Zhu
Pragmatics studies how context can contribute to language meanings.