ParallelCBF is a composable framework that unifies tensor-parallel UAV environments, hard-gate CBF safety filters, sharded BC-to-RL pipelines, and operational auditability as first-class APIs for safe reinforcement learning.
Improving reproducibility in machine learning research (a report from the neurips 2019 reproducibility program).Journal of machine learning research, 22(164):1–20
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
parallelcbf: A composable safety-filter and auditability framework for tensor-parallel reinforcement learning
ParallelCBF is a composable framework that unifies tensor-parallel UAV environments, hard-gate CBF safety filters, sharded BC-to-RL pipelines, and operational auditability as first-class APIs for safe reinforcement learning.