IEEE

Derivation of Mutual Information and Linear Minimum Mean-Square Error for Viterbi Decoding of Convolutional Codes Using the Innovations Method

Abstract: We apply the innovations method to Viterbi decoding of convolutional codes. First, we calculate the covariance matrix of the innovation (i.e., the soft-decision input to the main decoder in ...
IEEE

Kolmogorov Convolution Network: Knowledge Representation and Reasoning for Fault Diagnosis of Trolley Mechanism on Ship-to-Shore Cranes

Abstract: Accurate fault diagnosis of trolley mechanisms in ship-to-shore cranes is essential for ensuring cargo transportation at ports. While deep neural networks (DNNs) have made some achievements ...
GitHub

Diffusion Transformers with Representation Autoencoders (RAE)

We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...
GitHub

GaussianImage++: Boosted Image Representation and Compression with 2D Gaussian Splatting

After cloning the repository, you can follow these steps to train GaussianImage models under different tasks. If you encounter errors while installing the packages ...