activity
20132026
most citedInference of Probabilistic Programs with Moment-Matching Gaussian Mixtures

12 citations · 48 across the 23 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

math.OC2023

Proper Lumping for Positive Bilinear Control Systems

Antonio Jiménez-Pastor, Daniele Toller, Mirco Tribastone +2

Positive systems naturally arise in situations where the model tracks physical quantities. Although the linear case is well understood, analysis and controller design for nonlinear…

eess.SY2023

Coarse-graining Complex Networks for Control Equivalence

Daniele Toller, Mirco Tribastone, Max Tschaikowski +1

The ability to control complex networks is of crucial importance across a wide range of applications in natural and engineering sciences. However, issues of both theoretical and nu…

cs.PL2023★ 12 cited

Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures

Francesca Randone, Luca Bortolussi, Emilio Incerto +1

Computing the posterior distribution of a probabilistic program is a hard task for which no one-fit-for-all solution exists. We propose Gaussian Semantics, which approximates the e…

quant-ph2023★ 1 cited

Forward and Backward Constrained Bisimulations for Quantum Circuits using Decision Diagrams

Lukas Burgholzer, Antonio Jiménez-Pastor, Kim G. Larsen +3

Efficient methods for the simulation of quantum circuits on classic computers are crucial for their analysis due to the exponential growth of the problem size with the number of qu…

math.OC2023★ 2 cited

Certification of the proximal gradient method under fixed-point arithmetic for box-constrained QP problems

Pablo Krupa, Omar Inverso, Mirco Tribastone +1

In safety-critical applications that rely on the solution of an optimization problem, the certification of the optimization algorithm is of vital importance. Certification and subo…

eess.SY2023

Optimality-preserving Reduction of Chemical Reaction Networks

Kim G. Larsen, Daniele Toller, Mirco Tribastone +2

Across many disciplines, chemical reaction networks (CRNs) are an established population model defined as a system of coupled nonlinear ordinary differential equations. In many app…