5 papers · 1 filter
ExDBN: Learning Dynamic Bayesian Networks using Extended Mixed-Integer Programming Formulations
Pavel Rytir, Ales Wodecki, Georgios Korpas +1
Causal learning from data has received much attention recently. Bayesian networks can be used to capture causal relationships. There, one recovers a weighted directed acyclic graph…
Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons
Vyacheslav Kungurtsev, Fadwa Idlahcen, Petr Rysavy +2
In this paper, we present a guide to the foundations of learning Dynamic Bayesian Networks (DBNs) from data in the form of multiple samples of trajectories for some length of time.…
ExDAG: an MIQP Algorithm for Learning DAGs
Pavel Rytir, Ales Wodecki, Jakub Marecek
There has been a growing interest in causal learning in recent years. Commonly used representations of causal structures, including Bayesian networks and structural equation models…
Spectral Methods for Quantum Optimal Control: Artificial Boundary Conditions
Ales Wodecki, Jakub Marecek, Vyacheslav Kungurtsev +3
The problem of quantum state preparation is one of the main challenges in achieving the quantum advantage. Furthermore, classically, for multi-level problems, our ability to solve…
Learning quantum Hamiltonians at any temperature in polynomial time with Chebyshev and bit complexity
Ales Wodecki, Jakub Marecek
We consider the problem of learning local quantum Hamiltonians given copies of their Gibbs state at a known inverse temperature, following Haah et al. [2108.04842] and Bakshi et al…