6 citations · 15 across the 4 of their papers we have counts for
4 papers
Lessons From Red Teaming 100 Generative AI Products
Blake Bullwinkel, Amanda Minnich, Shiven Chawla +23
In recent years, AI red teaming has emerged as a practice for probing the safety and security of generative AI systems. Due to the nascency of the field, there are many open questi…
PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System
Gary D. Lopez Munoz, Amanda J. Minnich, Roman Lutz +17
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both s…
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows
Raphaël Pellegrin, Blake Bullwinkel, Marios Mattheakis +1
Physics-Informed Neural Networks (PINNs) offer a promising approach to solving differential equations and, more generally, to applying deep learning to problems in the physical sci…
DEQGAN: Learning the Loss Function for PINNs with Generative Adversarial Networks
Blake Bullwinkel, Dylan Randle, Pavlos Protopapas +1
Solutions to differential equations are of significant scientific and engineering relevance. Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving…