2 citations · 7 across the 5 of their papers we have counts for
6 papers
Neural Network-based OFDM Receiver for Resource Constrained IoT Devices
Nasim Soltani, Hai Cheng, Mauro Belgiovine +10
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the…
Equivariant Deep Dynamical Model for Motion Prediction
Bahar Azari, Deniz Erdoğmuş
Learning representations through deep generative modeling is a powerful approach for dynamical modeling to discover the most simplified and compressed underlying description of the…
PRRS Outbreak Prediction via Deep Switching Auto-Regressive Factorization Modeling
Mohammadsadegh Shamsabardeh, Bahar Azari, Beatriz Martínez-López
We propose an epidemic analysis framework for the outbreak prediction in the livestock industry, focusing on the study of the most costly and viral infectious disease in the swine…
Circular-Symmetric Correlation Layer based on FFT
Bahar Azari, Deniz Erdogmus
Despite the vast success of standard planar convolutional neural networks, they are not the most efficient choice for analyzing signals that lie on an arbitrarily curved manifold,…
Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting
Amirreza Farnoosh, Bahar Azari, Sarah Ostadabbas
We introduce deep switching auto-regressive factorization (DSARF), a deep generative model for spatio-temporal data with the capability to unravel recurring patterns in the data an…
Hypergraph-Based Analysis of Clustered Cooperative Beamforming with Application to Edge Caching
Bahar Azari, Osvaldo Simeone, Umberto Spagnolini +1
The evaluation of the performance of clustered cooperative beamforming in cellular networks generally requires the solution of complex non-convex optimization problems. In this let…