Tag: Quantum machine learning

A scale-matched benchmark finds that simulated hybrid quantum-classical neural networks match, but do not surpass, classical models and a simple ...

An open source toolkit called CohAlign predicts the first-order noise susceptibility of gradients in charge-conserving brickwork quantum neural networks from ...

A new review maps quantum algorithms onto every stage of drug discovery, quantifying the enormous hardware gap between today's noisy ...

A hybrid quantum-classical LSTM model achieved the highest reported accuracy for male infertility risk prediction while identifying daily sitting duration ...

A hybrid quantum-classical model outperformed XGBoost and other classical baselines in predicting ICU mortality across nearly 39,000 MIMIC-IV admissions, though ...

A new PLOS One study shows that combining quantum machine learning models with ontology matching raises Semantic Web Service discovery ...

Researchers in Vienna have redesigned dissipative quantum neural networks so each building block can implement any quantum channel, and shown ...

A new hybrid quantum-classical operator splitting method solves nonlinear parabolic PDEs up to 100 dimensions with provably faster convergence, promising ...

A new quantum encoding scheme called the permutation technique stores binary vectors in superposition and modifies Grover's algorithm to retrieve ...

Researchers at the Universidad de Salamanca have developed a Lie-algebraic framework that separates task-relevant signal from gradient geometry in variational ...