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Found 6 papers, 6 papers with code
Of Spiky SVDs and Music Recommendation
The truncated singular value decomposition is a widely used methodology in music recommendation for direct similar-item retrieval or embedding musical items for downstream tasks.
Learning Unsupervised Hierarchies of Audio Concepts
In this paper, we adapt concept learning to the realm of music, with its particularities.
Explainability in Music Recommender Systems
In this article, we discuss how explainability can be addressed in the context of MRSs.
Collaborative Filtering
Explainable artificial intelligence
+3
Towards Rigorous Interpretations: a Formalisation of Feature Attribution
Feature attribution is often loosely presented as the process of selecting a subset of relevant features as a rationale of a prediction.
Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction
Explaining recommendations enables users to understand whether recommended items are relevant to their needs and has been shown to increase their trust in the system.
MesoNet: a Compact Facial Video Forgery Detection Network
This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face.
