peteryschneider
AI/ML @Northrop Grumman
Northrop Grumman | Machine Learning and AutonomyLos Angeles, CA
Pinned Repositories
AIOS
AIOS: LLM Agent Operating System
telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
AIOS
AIOS: LLM Agent Operating System
art-aeroconf24
Repository on the Autonomous Rendezvous Transformer presented at the IEEE Aerospace Conference 2024
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
react-resume-template
A personal resume website template built with React.js, Typescript, Next.js, and styled with Tailwind css
telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
peteryschneider's Repositories
peteryschneider/AIOS
AIOS: LLM Agent Operating System
peteryschneider/art-aeroconf24
Repository on the Autonomous Rendezvous Transformer presented at the IEEE Aerospace Conference 2024
peteryschneider/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
peteryschneider/react-resume-template
A personal resume website template built with React.js, Typescript, Next.js, and styled with Tailwind css
peteryschneider/telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.