63 citations · 83 across the 5 of their papers we have counts for
5 papers
BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer
Piyush Jha, Joseph Scott, Jaya Sriram Ganeshna +2
We present a novel tool BertRLFuzzer, a BERT and Reinforcement Learning (RL) based fuzzer aimed at finding security vulnerabilities for Web applications. BertRLFuzzer works as foll…
Logic Guided Genetic Algorithms
Dhananjay Ashok, Joseph Scott, Sebastian Wetzel +2
We present a novel Auxiliary Truth enhanced Genetic Algorithm (GA) that uses logical or mathematical constraints as a means of data augmentation as well as to compute loss (in conj…
LGML: Logic Guided Machine Learning
Joseph Scott, Maysum Panju, Vijay Ganesh
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 funct…
Discovering Symmetry Invariants and Conserved Quantities by Interpreting Siamese Neural Networks
Sebastian J. Wetzel, Roger G. Melko, Joseph Scott +2
In this paper, we introduce interpretable Siamese Neural Networks (SNN) for similarity detection to the field of theoretical physics. More precisely, we apply SNNs to events in spe…
xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems
Vineel Nagisetty, Laura Graves, Joseph Scott +1
Generative Adversarial Networks (GANs) are a revolutionary class of Deep Neural Networks (DNNs) that have been successfully used to generate realistic images, music, text, and othe…