Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Conditioning Deep Generative Raw Audio Models for Structured Automatic Music
An End to End Model for Automatic Music Generation: Combining Deep Raw and Symbolic Audio Networks
Applying Learning Algorithms to Music Generation
Deep Learning Techniques for Music Generation - A Survey
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation
MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment
Deep Jammer : A Music Generation Model
Deep Learning for Music
Synthesizing Audio with GANs
Sequence to Sequence Autoencoders for Unsupervised Representation Learning from Audio
Restructuring of Deep Neural Network Acoustic Models with Singular Value Decomposition
Music Generation by Deep Learning - Challenges and Directions
Data augmentation for deep neural network acoustic modeling
Part-invariant Model for Music Generation and Harmonization
Deep recurrent music writer: Memory-enhanced variational autoencoder-based musical score composition and an objective measure
learning musical structure directly from sequences of music ∗ .
Feature learning and deep architectures: new directions for music informatics
Music transcription modelling and composition using deep learning
Pre-trained Deep Neural Network using Sparse Autoencoders and Scattering Wavelet Transform for Musical Genre Recognition
Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation
Bidirectional recurrent neural network language models for automatic speech recognition
automatic extraction of femur contours from hip x - ray images .
Neutron and photon spectra in LINACs
Advances in optimizing recurrent networks
Big data visualization: Tools and challenges