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This repository contains the code for the manuscript titled "Personalized pricing through Adversarial Risk Analysis"
A domain-general, Bayesian method for analyzing high-dimensional data tables
NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction
Implementation of Adversarial Multi-Distillation for Automatic Modulation Recognition Models.
[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
An Ontological Analysis and Redesign of the D3FEND Cybersecurity Model
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
We illustrate the use of adversarial risk analysis (ARA) for modelling a one-on-one air combat between pilots. We introduce a multi-stage sequential game to describe the decisions taken by the pilots.
Adversarial Risk Analysis for Improving Adversarial Training
TimeSHAP explains Recurrent Neural Network predictions.
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
A framework for modeling and simulating dynamical systems
Code for the paper: Adversarial Machine Learning: Bayesian Perspectives
A curated list of radar datasets, detection, tracking and fusion
Python functions and scripts to analyse cyclostationary signals
Python code translations for the book Collins, Travis F., Robin Getz, Di Pu, Alexander M. Wyglinski: Software-Defined Radio for Engineers
Radio modulation recognition with CNN, CLDNN, CGDNN and MCTransformer architectures. Best results were achieved with the CGDNN architecture, which has roughly 50,000 parameters, and the final model…
Radio Frequency Machine Learning with PyTorch