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Found 10 papers, 6 papers with code
Universal representation by Boltzmann machines with Regularised Axons
It is widely known that Boltzmann machines are capable of representing arbitrary probability distributions over the values of their visible neurons, given enough hidden ones.
TensorKrowch: Smooth integration of tensor networks in machine learning
Tensor networks are factorizations of high-dimensional tensors into networks of smaller tensors.
Accelerating the training of single-layer binary neural networks using the HHL quantum algorithm
The solution is encoded in superposition at the output of a quantum circuit.
Privacy-preserving machine learning with tensor networks
Tensor networks, widely used for providing efficient representations of low-energy states of local quantum many-body systems, have been recently proposed as machine learning architectures which could present advantages with respect to traditional ones.
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines
We find improvements ranging from 5% to 72% against attacks with Boltzmann machines on the MNIST dataset.
Efficient training of energy-based models via spin-glass control
We introduce a new family of energy-based probabilistic graphical models for efficient unsupervised learning.
Quantum Inflation: A General Approach to Quantum Causal Compatibility
Causality is a seminal concept in science: Any research discipline, from sociology and medicine to physics and chemistry, aims at understanding the causes that could explain the correlations observed among some measured variables.
Bounding the sets of classical and quantum correlations in networks
We present a method that allows the study of classical and quantum correlations in networks with causally-independent parties, such as the scenario underlying entanglement swapping.
Quantum Physics
Bayesian Deep Learning on a Quantum Computer
Furthermore, we demonstrate the execution of the algorithm on contemporary quantum computers and analyze its robustness with respect to realistic noise models.
A quantum Otto engine with finite heat baths: energy, correlations, and degradation
We study a driven harmonic oscillator operating an Otto cycle between two thermal baths of finite size.
Quantum Physics Statistical Mechanics
