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Found 6 papers, 4 papers with code
Tokenize Anything via Prompting
The semantic token is responsible for learning the semantic priors in a predefined concept space.
Representation Learning on Heterostructures via Heterogeneous Anonymous Walks
Capturing structural similarity has been a hot topic in the field of network embedding recently due to its great help in understanding the node functions and behaviors.
Iterative Self-consistent Parallel Magnetic Resonance Imaging Reconstruction based on Nonlocal Low-Rank Regularization
Recent methods have exploited the nonlocal self-similarity (NSS) of images by imposing nonlocal low-rankness of similar patches to achieve a superior performance.
A Survey on Role-Oriented Network Embedding
A wide variety of NE methods focus on the proximity of networks.
Taylor saves for later: disentanglement for video prediction using Taylor representation
We propose a two-branch seq-to-seq deep model to disentangle the Taylor feature and the residual feature in video frames by a novel recurrent prediction module (TaylorCell) and residual module.
Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework
Deep Learning has made a great progress for these years.
