2 papers
cs.CV2026
CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws
Adnan Harun Doğan, Mert Deniz, Hande Alemdar +1
We present CoFINN (Conservation Flux Informed Neural Networks), a physics-informed deep learning framework for predicting compressible flow fields governed by conservation laws. Un…
cs.LG2016
Ternary Neural Networks for Resource-Efficient AI Applications
Hande Alemdar, Vincent Leroy, Adrien Prost-Boucle +1
The computation and storage requirements for Deep Neural Networks (DNNs) are usually high. This issue limits their deployability on ubiquitous computing devices such as smart phone…