Publications (11)
Convolutional Filtering and Neural Networks with Non Commutative Algebras
Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro
In this paper we introduce and study the algebraic generalization of non commutative convolutional neural networks. We leverage the theory of algebraic signal processing to model c…
Learning Connectivity for Data Distribution in Robot Teams
Ekaterina Tolstaya, Landon Butler, Daniel Mox +3
Many algorithms for control of multi-robot teams operate under the assumption that low-latency, global state information necessary to coordinate agent actions can readily be dissem…
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin Singh Kang, Landon Butler, Abhineet Agarwal +4
Large language models (LLMs) have revolutionized machine learning due to their ability to capture complex interactions between input features. Popular post-hoc explanation methods…
Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations
Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro
In this paper we discuss the results recently published in~[1] about algebraic signal models (ASMs) based on non commutative algebras and their use in convolutional neural networks…
Convolutional Learning on Multigraphs
Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro
Graph convolutional learning has led to many exciting discoveries in diverse areas. However, in some applications, traditional graphs are insufficient to capture the structure and…
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
Landon Butler, Abhineet Agarwal, Justin Singh Kang +3
Large Language Models (LLMs) have achieved remarkable performance by capturing complex interactions between input features. To identify these interactions, most existing approaches…