
-
Federated Quantum Machine Learning
Distributed training across several quantum computers could significantl...
read it
-
Quantum machine learning with differential privacy
Quantum machine learning (QML) can complement the growing trend of using...
read it
-
An end-to-end trainable hybrid classical-quantum classifier
We introduce a hybrid model combining a quantum-inspired tensor network ...
read it
-
Hybrid Quantum-Classical Graph Convolutional Network
The high energy physics (HEP) community has a long history of dealing wi...
read it
-
Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
This work presents a quantum convolutional neural network (QCNN) for the...
read it
-
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
One key step in performing quantum machine learning (QML) on noisy inter...
read it
-
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition
We propose a novel decentralized feature extraction approach in federate...
read it
-
Quantum Long Short-Term Memory
Long short-term memory (LSTM) is a kind of recurrent neural networks (RN...
read it
-
Adversarial Robustness of Deep Convolutional Candlestick Learner
Deep learning (DL) has been applied extensively in a wide range of field...
read it
-
Data Augmentation for Deep Candlestick Learner
To successfully build a deep learning model, it will need a large amount...
read it
-
Explainable Deep Convolutional Candlestick Learner
Candlesticks are graphical representations of price movements for a give...
read it
-
Variational Quantum Circuits and Deep Reinforcement Learning
Recently, machine learning has prevailed in many academia and industrial...
read it