3 papers
eess.SY2026
Myopically Verifiable Probabilistic Certificates for Safe Control and Learning
Zhuoyuan Wang, Haoming Jing, Christian Kurniawan +2
This paper addresses the design of safety certificates for stochastic systems, with a focus on ensuring long-term safety through fast real-time control. In stochastic environments,…
cs.LG2025
Kalman Bayesian Transformer
Haoming Jing, Oren Wright, José M. F. Moura +1
Sequential fine-tuning of transformers is useful when new data arrive sequentially, especially with shifting distributions. Unlike batch learning, sequential learning demands that…
eess.SY2025
Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics
Haoming Jing, Yorie Nakahira
Many systems contain latent variables that make their dynamics partially unidentifiable or cause distribution shifts in the observed statistics between offline and online data. How…