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Found 4 papers, 4 papers with code
RBF-PINN: Non-Fourier Positional Embedding in Physics-Informed Neural Networks
While many recent Physics-Informed Neural Networks (PINNs) variants have had considerable success in solving Partial Differential Equations, the empirical benefits of feature mapping drawn from the broader Neural Representations research have been largely overlooked.
Training dynamics in Physics-Informed Neural Networks with feature mapping
Physics-Informed Neural Networks (PINNs) have emerged as an iconic machine learning approach for solving Partial Differential Equations (PDEs).
Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation
This paper presents a deep learning framework for medical video segmentation.
Video-TransUNet: Temporally Blended Vision Transformer for CT VFSS Instance Segmentation
Our findings suggest that the proposed model can indeed enhance the TransUNet architecture via exploiting temporal information and improving segmentation performance by a significant margin.
