The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
We show how to improve a state-of-the-art neural network language model that converts the previous "context" words into feature vectors and combines these feature vectors...
Background: RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily co...
Background: Many structural properties such as solvent accessibility, dihedral angles and helix-helix contacts can be assigned to each residue in a membrane protein. Independent s...
In this paper we combine model-based video synthesis with block-based motion-compensated prediction (MCP). Two frames are utilized far prediction where one frame is the previous d...