1 citations · 1 across the 5 of their papers we have counts for
5 papers
Sparse Interpretable Deep Learning with LIES Networks for Symbolic Regression
Mansooreh Montazerin, Majd Al Aawar, Antonio Ortega +1
Symbolic regression (SR) aims to discover closed-form mathematical expressions that accurately describe data, offering interpretability and analytical insight beyond standard black…
SWAT-NN: Simultaneous Weights and Architecture Training for Neural Networks in a Latent Space
Zitong Huang, Mansooreh Montazerin, Ajitesh Srivastava
Designing neural networks typically relies on manual trial and error or a neural architecture search (NAS) followed by weight training. The former is time-consuming and labor-inten…
Simultaneous Weight and Architecture Optimization for Neural Networks
Zitong Huang, Mansooreh Montazerin, Ajitesh Srivastava
Neural networks are trained by choosing an architecture and training the parameters. The choice of architecture is often by trial and error or with Neural Architecture Search (NAS)…
Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks
Majd Al Aawar, Srikar Mutnuri, Mansooreh Montazerin +1
During the COVID-19 pandemic, a major driver of new surges has been the emergence of new variants. When a new variant emerges in one or more countries, other nations monitor its sp…
Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable?
Sarthak Kumar Maharana, Krishna Kamal Adidam, Shoumik Nandi +1
Acoustic-to-articulatory inversion (AAI) involves mapping from the acoustic to the articulatory space. Signal-processing features like the MFCCs, have been widely used for the AAI…