Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior
Fast and robust fixed-point algorithms for independent component analysis
Gaussian Mixture Models
Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization
Blind separation of speech mixtures via time-frequency masking
An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems
Group delay based music source separation using deep recurrent neural networks
Maximum Likelihood Sound Source Localization and Beamforming for Directional Microphone Arrays in Distributed Meetings
Independent Component Analysis : Algorithms and Applications
Low latency sound source separation using convolutional recurrent neural networks
Generalized State Coherence Transform for multidimensional localization of multiple sources
The subspace Gaussian mixture model - A structured model for speech recognition
Single-Channel Multi-Speaker Separation using Deep Clustering
Monaural Audio Speaker Separation with Source Contrastive Estimation
Matrix manifold optimization for Gaussian mixtures
Secure data communication using blind source separation
Bayesian Singing-Voice Separation
Approximate expressions for the mean and the covariance of the maximum likelihood estimator for acoustic source localization
Group sparse coding with a laplacian scale mixture prior
Learning Echo Paths During Continuous Double-Talk Using Semi-Blind Source Separation
A Bayesian Filtering Algorithm for Gaussian Mixture Models
MiBench: A free, commercially representative embedded benchmark suite
A systematic review of Functional Communication Training (FCT) interventions involving augmentative and alternative communication in school settings.
Synthetic Aperture Radar Image Processing using the Supervised Textural-Neural Network Classification Algorithm
A rare case of oral multisystem Langerhans cell histiocytosis
Emergence of simple-cell receptive field properties by learning a sparse code for natural images