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05/09/2023
Attention-Based Transformer Networks for Quantum State Tomography
Neural networks have been actively explored for quantum state tomography...
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02/28/2023
Auxiliary Task-based Deep Reinforcement Learning for Quantum Control
Due to its property of not requiring prior knowledge of the environment,...
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05/22/2022
A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning
While reinforcement learning (RL) algorithms are achieving state-of-the-...
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04/16/2022
Efficient Bayesian Policy Reuse with a Scalable Observation Model in Deep Reinforcement Learning
Bayesian policy reuse (BPR) is a general policy transfer framework for s...
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03/06/2022
Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation
Multi-agent settings remain a fundamental challenge in the reinforcement...
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08/19/2021
Residual Tensor Train: a Flexible and Efficient Approach for Learning Multiple Multilinear Correlations
Tensor Train (TT) approach has been successfully applied in the modellin...
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04/15/2021
Rule-Based Reinforcement Learning for Efficient Robot Navigation with Space Reduction
For real-world deployments, it is critical to allow robots to navigate i...
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01/06/2021
Deep Reinforcement Learning with Quantum-inspired Experience Replay
In this paper, a novel training paradigm inspired by quantum computation...
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12/31/2020
Curriculum-based Deep Reinforcement Learning for Quantum Control
Deep reinforcement learning has been recognized as an efficient techniqu...
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10/09/2020
Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments
Evolution strategies (ES), as a family of black-box optimization algorit...
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08/23/2020
Quantum Language Model with Entanglement Embedding for Question Answering
Quantum Language Models (QLMs) in which words are modelled as quantum su...
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07/28/2020
Lifelong Incremental Reinforcement Learning with Online Bayesian Inference
A central capability of a long-lived reinforcement learning (RL) agent i...
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06/15/2020
Derivative-free global minimization for a class of multiple minima problems
We prove that the finite-difference based derivative-free descent (FD-DF...
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05/22/2020
On compression rate of quantum autoencoders: Control design, numerical and experimental realization
Quantum autoencoders which aim at compressing quantum information in a l...
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06/08/2018
Fidelity-based Probabilistic Q-learning for Control of Quantum Systems
The balance between exploration and exploitation is a key problem for re...
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02/13/2017
Differential Evolution for Quantum Robust Control: Algorithm, Applications and Experiments
Robust control design for quantum systems has been recognized as a key t...
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09/07/2016