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Found 5 papers, 2 papers with code
BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer
We present a novel tool BertRLFuzzer, a BERT and Reinforcement Learning (RL) based fuzzer aimed at finding security vulnerabilities for Web applications.
Logic Guided Genetic Algorithms
Our method, logic-guided genetic algorithm (LGGA), takes as input a set of labelled data points and auxiliary truths (ATs) (mathematical facts known a priori about the unknown function the regressor aims to learn) and outputs a specially generated and curated dataset that can be used with any SR method.
LGML: Logic Guided Machine Learning
We introduce Logic Guided Machine Learning (LGML), a novel approach that symbiotically combines machine learning (ML) and logic solvers with the goal of learning mathematical functions from data.
Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks
It turns out that in the process of learning which datapoints belong to the same event or field configuration, these SNNs also learn the relevant symmetry invariants and conserved quantities.
xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems
A potential weakness in GANs is that it requires a lot of data for successful training and data collection can be an expensive process.
