Search Results for author:
Found 2 papers, 1 papers with code
State-Free Inference of State-Space Models: The Transfer Function Approach
We approach designing a state-space model for deep learning applications through its dual representation, the transfer function, and uncover a highly efficient sequence parallel inference algorithm that is state-free: unlike other proposed algorithms, state-free inference does not incur any significant memory or computational cost with an increase in state size.
Expandable YOLO: 3D Object Detection from RGB-D Images
This paper aims at constructing a light-weight object detector that inputs a depth and a color image from a stereo camera.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
