activity
20242026
collaborators

6 papers

cs.LG2026

DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces

Romeo Valentin, Sydney M. Katz, Vincent Vanhoucke +1

Dictionary learning has recently emerged as a promising approach for mechanistic interpretability of large transformer models. Disentangling high-dimensional transformer embeddings…

cs.AI2026

The FABRIC Strategy for Verifying Neural Feedback Systems

Samuel I. Akinwande, Sydney M. Katz, Mykel J. Kochenderfer +1

Forward reachability analysis is a dominant approach for verifying reach-avoid specifications in neural feedback systems, i.e., dynamical systems controlled by neural networks, and…

cs.AI2026

A New Strategy for Verifying Reach-Avoid Specifications in Neural Feedback Systems

Samuel I. Akinwande, Sydney M. Katz, Mykel J. Kochenderfer +1

Forward reachability analysis is the predominant approach for verifying reach-avoid properties in neural feedback systems (dynamical systems controlled by neural networks). This do…

cs.RO2025

Aircraft Collision Avoidance Systems: Technological Challenges and Solutions on the Path to Regulatory Acceptance

Sydney M. Katz, Robert J. Moss, Dylan M. Asmar +3

Aircraft collision avoidance systems is critical to modern aviation. These systems are designed to predict potential collisions between aircraft and recommend appropriate avoidance…

cs.CV2025

Predictive Uncertainty for Runtime Assurance of a Real-Time Computer Vision-Based Landing System

Romeo Valentin, Sydney M. Katz, Artur B. Carneiro +2

Recent advances in data-driven computer vision have enabled robust autonomous navigation capabilities for civil aviation, including automated landing and runway detection. However,…

cs.RO2024

Failure Probability Estimation for Black-Box Autonomous Systems using State-Dependent Importance Sampling Proposals

Harrison Delecki, Sydney M. Katz, Mykel J. Kochenderfer

Estimating the probability of failure is a critical step in developing safety-critical autonomous systems. Direct estimation methods such as Monte Carlo sampling are often impracti…