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20222026
most citedNeural Networks Reduction via Lumping

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.LO2026

A Lumpability-Driven Taxonomy of Strong and Weak Stochastic Bisimilarities with Their Congruence Properties

Riccardo Romanello, Andrea Esposito, Marco Bernardo +2

We study the relationships among the stochastic bisimulation-style equivalences over PEPA - Performance Evaluation Process Algebra definable according to the well known notions of…

cs.AI2026

AlphaCNOT: Learning CNOT Minimization with Model-Based Planning

Jacopo Cossio, Daniele Lizzio Bosco, Riccardo Romanello +2

Quantum circuit optimization is a central task in quantum computing, as current NISQ devices suffer from error propagation that often scales with the number of operations. Among qu…

cs.AI2025

CNOT Minimal Circuit Synthesis: A Reinforcement Learning Approach

Riccardo Romanello, Daniele Lizzio Bosco, Jacopo Cossio +4

CNOT gates are fundamental to quantum computing, as they facilitate entanglement, a crucial resource for quantum algorithms. Certain classes of quantum circuits are constructed exc…

cs.PF2025

Exact Persistent Stochastic Non-Interference

Carla Piazza, Riccardo Romanello, Sabina Rossi

Persistent Stochastic Non-Interference (PSNI) was introduced to capture a quantitative security property in stochastic process algebras, ensuring that a high-level process does not…

cs.LG2022★ 1 cited

Neural Networks Reduction via Lumping

Dalila Ressi, Riccardo Romanello, Sabina Rossi +1

The increasing size of recently proposed Neural Networks makes it hard to implement them on embedded devices, where memory, battery and computational power are a non-trivial bottle…