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Found 9 papers, 2 papers with code
Jet Discrimination with Quantum Complete Graph Neural Network
Machine learning, particularly deep neural networks, has been widely utilized in high energy physics and has shown remarkable results in various applications.
Real Time On Sensor Gait Phase Detection with 0.5KB Deep Learning Model
Gait phase detection with convolution neural network provides accurate classification but demands high computational cost, which inhibits real time low power on-sensor processing.
Automatic Melody Harmonization with Triad Chords: A Comparative Study
Several prior works have proposed various methods for the task of automatic melody harmonization, in which a model aims to generate a sequence of chords to serve as the harmonic accompaniment of a given multiple-bar melody sequence.
Musical Composition Style Transfer via Disentangled Timbre Representations
We investigate disentanglement techniques such as adversarial training to separate latent factors that are related to the musical content (pitch) of different parts of the piece, and that are related to the instrumentation (timbre) of the parts per short-time segment.
Audio and Speech Processing Sound
Representation Learning for Image-based Music Recommendation
Image perception is one of the most direct ways to provide contextual information about a user concerning his/her surrounding environment; hence images are a suitable proxy for contextual recommendation.
Superhighway: Bypass Data Sparsity in Cross-Domain CF
Cross-domain collaborative filtering (CF) aims to alleviate data sparsity in single-domain CF by leveraging knowledge transferred from related domains.
Vertex-Context Sampling for Weighted Network Embedding
Many existing methods adopt a uniform sampling method to reduce learning complexity, but when the network is non-uniform (i. e. a weighted network) such uniform sampling incurs information loss.
Hit Song Prediction for Pop Music by Siamese CNN with Ranking Loss
A model for hit song prediction can be used in the pop music industry to identify emerging trends and potential artists or songs before they are marketed to the public.
Revisiting the problem of audio-based hit song prediction using convolutional neural networks
Being able to predict whether a song can be a hit has impor- tant applications in the music industry.
