Temporal causal models encode Linear Bounded Automata for context-sensitive languages and become Turing complete with countably infinite variables.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Observable Neural ODEs link control-theoretic observability to causal identifiability for continuous-time treatment effect forecasting.
citing papers explorer
-
Temporal Causal Models as a Model of Computation
Temporal causal models encode Linear Bounded Automata for context-sensitive languages and become Turing complete with countably infinite variables.
-
Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
Observable Neural ODEs link control-theoretic observability to causal identifiability for continuous-time treatment effect forecasting.