In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
The main difficulty in the formalization of a static analysis framework for CC programs is probably related to the correct approximation of the entailment relation between constrai...
A major problem in magnetic resonance imaging (MRI) is the lack of a pulse sequence dependent standardized intensity scale like the Hounsfield units in computed tomography. This af...
We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...
We conjecture that the worst case number of experiments necessary and sufficient to discover a causal graph uniquely given its observational Markov equivalence class can be specif...