1 citations · 1 across the 8 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2026
Neural Scaling Laws of Transformer Operator Network
Haoran Yan, Zhongjie Shi, Yuanzhe Xi +2
Transformers have emerged as powerful architectures for learning solution operators of physical systems. Empirically the prediction error has been observed to decrease when the dat…
stat.ML2025
Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics
Biraj Dahal, Jiahui Cheng, Hao Liu +2
Many problems in science and engineering involve time-dependent, high dimensional datasets arising from complex physical processes, which are costly to simulate. In this work, we p…
stat.ML2024
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
Hao Liu, Jiahui Cheng, Wenjing Liao
Deep learning has exhibited remarkable results across diverse areas. To understand its success, substantial research has been directed towards its theoretical foundations. Neverthe…