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07/21/2023
Persistent Ballistic Entanglement Spreading with Optimal Control in Quantum Spin Chains
Entanglement propagation provides a key routine to understand quantum ma...
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05/10/2023
Compressing neural network by tensor network with exponentially fewer variational parameters
Neural network (NN) designed for challenging machine learning tasks is i...
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03/11/2023
Intelligent diagnostic scheme for lung cancer screening with Raman spectra data by tensor network machine learning
Artificial intelligence (AI) has brought tremendous impacts on biomedica...
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08/08/2022
Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations
Applying artificial intelligence to scientific problems (namely AI for s...
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07/13/2022
Unsupervised Recognition of Informative Features via Tensor Network Machine Learning and Quantum Entanglement Variations
Given an image of a white shoe drawn on a blackboard, how are the white ...
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03/29/2022
Circuit encapsulation for efficient quantum computing based on controlled many-body dynamics
Controlling the time evolution of interacting spin systems is an importa...
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07/01/2021
Non-parametric Active Learning and Rate Reduction in Many-body Hilbert Space with Rescaled Logarithmic Fidelity
In quantum and quantum-inspired machine learning, the very first step is...
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06/06/2021
Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling
The hybridizations of machine learning and quantum physics have caused e...
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06/03/2021
Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions
State preparation is of fundamental importance in quantum physics, which...
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04/30/2021
Automatically Differentiable Quantum Circuit for Many-qubit State Preparation
Constructing quantum circuits for efficient state preparation belongs to...
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12/22/2020
Residual Matrix Product State for Machine Learning
Tensor network (TN), which originates from quantum physics, shows broad ...
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12/05/2020
Deep neural network predicts parameters of quantum many-body Hamiltonians by learning visualized wave-functions
In the past decades, methods to solve the ground state given a quantum m...
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01/10/2020
Tangent-Space Gradient Optimization of Tensor Network for Machine Learning
The gradient-based optimization method for deep machine learning models ...
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12/30/2019
Bayesian Tensor Network and Optimization Algorithm for Probabilistic Machine Learning
Describing or calculating the conditional probabilities of multiple even...
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12/30/2019
Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning
It is known that describing or calculating the conditional probabilities...
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07/24/2019
Quantum Compressed Sensing with Unsupervised Tensor Network Machine Learning
We propose tensor-network compressed sensing (TNCS) for compressing and ...
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03/26/2019
Generative Tensor Network Classification Model for Supervised Machine Learning
Tensor network (TN) has recently triggered extensive interests in develo...
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03/24/2018
Learning architectures based on quantum entanglement: a simple matrix product state algorithm for image recognition
It is a fundamental, but still elusive question whether methods based on...
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10/13/2017