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Found 4 papers, 3 papers with code
Online Convex Optimization of Programmable Quantum Computers to Simulate Time-Varying Quantum Channels
Simulating quantum channels is a fundamental primitive in quantum computing, since quantum channels define general (trace-preserving) quantum operations.
Quantum Machine Learning for Distributed Quantum Protocols with Local Operations and Noisy Classical Communications
Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC).
Learning Quantum Entanglement Distillation with Noisy Classical Communications
Therefore, an important primitive for quantum networking is entanglement distillation, whose goal is to enhance the fidelity of entangled qubits through local operations and classical communication (LOCC).
Robust Distributed Bayesian Learning with Stragglers via Consensus Monte Carlo
This paper studies distributed Bayesian learning in a setting encompassing a central server and multiple workers by focusing on the problem of mitigating the impact of stragglers.
