7 citations · 10 across the 5 of their papers we have counts for
5 papers
SPUS: A Lightweight and Parameter-Efficient Foundation Model for PDEs
Abu Bucker Siddik, Diane Oyen, Alexander Most +2
We introduce Small PDE U-Net Solver (SPUS), a compact and efficient foundation model (FM) designed as a unified neural operator for solving a wide range of partial differential equ…
LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study
Nishath Rajiv Ranasinghe, Shawn M. Jones, Michal Kucer +5
Large Language Models (LLMs) are increasingly being leveraged for generating and translating scientific computer codes by both domain-experts and non-domain experts. Fortran has se…
DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding
Kehinde Ajayi, Xin Wei, Martin Gryder +5
Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still…
Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space
Diane Oyen, Michal Kucer, Nick Hengartner +1
Machine learning classifiers have been demonstrated, both empirically and theoretically, to be robust to label noise under certain conditions -- notably the typical assumption is t…
On visual self-supervision and its effect on model robustness
Michal Kucer, Diane Oyen, Garrett Kenyon
Recent self-supervision methods have found success in learning feature representations that could rival ones from full supervision, and have been shown to be beneficial to the mode…