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Found 9 papers, 1 papers with code
Quantum Theory and Application of Contextual Optimal Transport
In cases where paired data measurements ($\mu$, $\nu$) are coupled to a context variable $p_i$ , one may aspire to learn a global transportation map that can be parameterized through a potentially unseen con-text.
Symmetry-invariant quantum machine learning force fields
Our results suggest that molecular force fields generation can significantly profit from leveraging the framework of geometric quantum machine learning, and that chemical systems represent, in fact, an interesting and rich playground for the development and application of advanced quantum machine learning tools.
Unravelling physics beyond the standard model with classical and quantum anomaly detection
Much hope for finding new physics phenomena at microscopic scale relies on the observations obtained from High Energy Physics experiments, like the ones performed at the Large Hadron Collider (LHC).
Quantum Machine Learning Framework for Virtual Screening in Drug Discovery: a Prospective Quantum Advantage
Machine Learning (ML) for Ligand Based Virtual Screening (LB-VS) is an important in-silico tool for discovering new drugs in a faster and cost-effective manner, especially for emerging diseases such as COVID-19.
Analytic theory for the dynamics of wide quantum neural networks
We define wide quantum neural networks as parameterized quantum circuits in the limit of a large number of qubits and variational parameters.
Quantum neural networks force fields generation
Accurate molecular force fields are of paramount importance for the efficient implementation of molecular dynamics techniques at large scales.
Representation Learning via Quantum Neural Tangent Kernels
We analytically solve the dynamics in the frozen limit, or lazy training regime, where variational angles change slowly and a linear perturbation is good enough.
Variational learning for quantum artificial neural networks
In the last few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information processing systems can be realized and programmed.
Quantum Physics
An Artificial Neuron Implemented on an Actual Quantum Processor
Artificial neural networks are the heart of machine learning algorithms and artificial intelligence protocols.
Quantum Physics
