Reilly Cannon

According to our database, Reilly Cannon authored at least 5 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Measuring Training Variability From Stochastic Optimization Using Robust Nonparametric Testing.

Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate

IEEE J. Sel. Top. Signal Process., October, 2025

Assessing Generative Models for Structured Data.

Reilly Cannon, Nicolette M. Laird, Caesar Vazquez, Andy Lin, Amy Wagler, Tony Chiang

CoRR, March, 2025

2024

Understanding Generative AI Content with Embedding Models.

Max Vargas, Reilly Cannon, Andrew Engel, Anand D. Sarwate, Tony Chiang

CoRR, 2024

Measuring model variability using robust non-parametric testing.

Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate

CoRR, 2024

2023

Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks.

Sinjini Banerjee, Reilly Cannon, Tim Marrinan, Tony Chiang, Anand D. Sarwate

CoRR, 2023