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Found 10 papers, 8 papers with code
Modeling the Music Genre Perception across Language-Bound Cultures
The music genre perception expressed through human annotations of artists or albums varies significantly across language-bound cultures.
Cultural Vocal Bursts Intensity Prediction
Information Retrieval
+2
Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation
However, without a parallel corpus, previous solutions could not handle tag systems in other languages, being limited to the English-language only.
Carousel Personalization in Music Streaming Apps with Contextual Bandits
Media services providers, such as music streaming platforms, frequently leverage swipeable carousels to recommend personalized content to their users.
Muzeeglot : annotation multilingue et multi-sources d'entit\'es musicales \`a partir de repr\'esentations de genres musicaux (Muzeeglot : cross-lingual multi-source music item annotation from music genre embeddings)
Au sein de cette d{\'e}monstration, nous pr{\'e}sentons Muzeeglot, une interface web permettant de visualiser des espaces de repr{\'e}sentations de genres musicaux provenant de sources vari{\'e}es et de langues diff{\'e}rentes.
FastGAE: Scalable Graph Autoencoders with Stochastic Subgraph Decoding
Graph autoencoders (AE) and variational autoencoders (VAE) are powerful node embedding methods, but suffer from scalability issues.
Simple and Effective Graph Autoencoders with One-Hop Linear Models
Over the last few years, graph autoencoders (AE) and variational autoencoders (VAE) emerged as powerful node embedding methods, with promising performances on challenging tasks such as link prediction and node clustering.
Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks
Graph autoencoders (AE) and variational autoencoders (VAE) recently emerged as powerful node embedding methods, with promising performances on challenging tasks such as link prediction and node clustering.
Gravity-Inspired Graph Autoencoders for Directed Link Prediction
Graph autoencoders (AE) and variational autoencoders (VAE) recently emerged as powerful node embedding methods.
A Degeneracy Framework for Scalable Graph Autoencoders
In this paper, we present a general framework to scale graph autoencoders (AE) and graph variational autoencoders (VAE).
Adaptive Submodular Influence Maximization with Myopic Feedback
This paper examines the problem of adaptive influence maximization in social networks.
Social and Information Networks
