48 citations · 65 across the 8 of their papers we have counts for
8 papers
Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations
Michael Harradon, Jeff Druce, Brian Ruttenberg
Deep neural networks are complex and opaque. As they enter application in a variety of important and safety critical domains, users seek methods to explain their output predictions…
Artificial Intelligence Based Malware Analysis
Avi Pfeffer, Brian Ruttenberg, Lee Kellogg +12
Artificial intelligence methods have often been applied to perform specific functions or tasks in the cyber-defense realm. However, as adversary methods become more complex and dif…
Structured Factored Inference: A Framework for Automated Reasoning in Probabilistic Programming Languages
Avi Pfeffer, Brian Ruttenberg, William Kretschmer
Reasoning on large and complex real-world models is a computationally difficult task, yet one that is required for effective use of many AI applications. A plethora of inference al…
Probabilistic Programming for Malware Analysis
Brian Ruttenberg, Lee Kellogg, Avi Pfeffer
Constructing lineages of malware is an important cyber-defense task. Performing this task is difficult, however, due to the amount of malware data and obfuscation techniques by the…
Lazy Factored Inference for Functional Probabilistic Programming
Avi Pfeffer, Brian Ruttenberg, Amy Sliva +2
Probabilistic programming provides the means to represent and reason about complex probabilistic models using programming language constructs. Even simple probabilistic programs ca…
Decision-Making with Complex Data Structures using Probabilistic Programming
Brian E. Ruttenberg, Avi Pfeffer
Existing decision-theoretic reasoning frameworks such as decision networks use simple data structures and processes. However, decisions are often made based on complex data structu…
A Latent Parameter Node-Centric Model for Spatial Networks
Nicholas D. Larusso, Brian E. Ruttenberg, Ambuj Singh
Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of complex systems. For example, many social networks attach geo-location informati…
Indexing the Earth Mover's Distance Using Normal Distributions
Brian E. Ruttenberg, Ambuj K. Singh
Querying uncertain data sets (represented as probability distributions) presents many challenges due to the large amount of data involved and the difficulties comparing uncertainty…