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Found 4 papers, 1 papers with code
GINA: Neural Relational Inference From Independent Snapshots
Dynamical systems in which local interactions among agents give rise to complex emerging phenomena are ubiquitous in nature and society.
Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models
To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part.
Analysis of Markov Jump Processes under Terminal Constraints
Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints.
Tracking the Race Between Deep Reinforcement Learning and Imitation Learning -- Extended Version
Our evaluations show that for this sequential decision making problem, deep reinforcement learning performs best in many aspects even though for imitation learning optimal decisions are considered.
