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Found 5 papers, 3 papers with code
LOCOST: State-Space Models for Long Document Abstractive Summarization
State-space models are a low-complexity alternative to transformers for encoding long sequences and capturing long-term dependencies.
Learning from Multiple Sources for Data-to-Text and Text-to-Data
Our model is designed to handle the tasks of D2T and T2D jointly.
Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models
We present a dual-view mixture model to cluster users based on their features and latent behavioral functions.
Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization
In some cases, the analysis of binary matrices can be tackled with nonnegative matrix factorization (NMF), where the observed data matrix is approximated by the product of two smaller nonnegative matrices.
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
We present novel understandings of the Gamma-Poisson (GaP) model, a probabilistic matrix factorization model for count data.
