Research
The ISPAMM laboratory is active in the following fields.
Machine Learning for scientific discovery
Machine Learning for scientific discovery
Graph neural networks and geometric deep learning
Continual learning for neural networks
Modular and dynamic neural networks
Generative Deep learning
Generative Deep learning
Image and audio generation
Speech to pose
Image Editing
Super Resolution
advanced neural networks
advanced neural networks
Multimodal medical applications
Neural networks in hypercomplex domains
Smart water metering
Digital twins
Signal processing
Signal processing
Linear and nonlinear filtering.
Non-linear spline filtering.
Signal processing in the frequency and hyper-complex domains.
Array processing.
Computational intelligence
Computational intelligence
Distributed learning.
Random feature extraction.
Learning with big data.
Evolutionary methods for learning.
Applications
Applications
Beamforming.
Acoustic echo cancellation.
Quality enhancement.
Interactive audio optimization.
Audio classification.