Quantum Physic

Quantum physics is currently driving innovation in machine learning and optimization, aiming to leverage quantum phenomena for computational advantages over classical approaches. Research focuses on developing and testing hybrid quantum-classical algorithms, including quantum neural networks (QNNs), variational quantum regressors (VQRs), and quantum-enhanced versions of classical algorithms like support vector machines and evolutionary algorithms, often applied to problems in image classification, medical diagnostics, and optimization tasks. These efforts are significant because they could lead to breakthroughs in fields like drug discovery, materials science, and cybersecurity by enabling faster and more efficient solutions to complex problems currently intractable for classical computers.

Papers

May 4, 2023

Trainability barriers and opportunities in quantum generative modeling
Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Sofia Vallecorsa, Michele Grossi, Zoë Holmes
Generative Modeling Emerging Opportunity Quantum Physic Quantum Circuit Quantum Hardware Planning Loss Implicit Generative

April 25, 2023

The cross-sectional stock return predictions via quantum neural network and tensor network
Nozomu Kobayashi, Yoshiyuki Suimon, Koichi Miyamoto, Kosuke Mitarai
Neural Network Human Prediction Quantum Physic Quantum Neural Network Stock Market Stock Return Prediction Quantum Inspired Machine Learning Model Benchmark Scalable Quantum

April 20, 2023

Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana, André Röhm, Ryoichi Horisaki, Makoto Naruse
Multi Armed Bandit Environment Exploration Quantum Physic Bandit Algorithm Random Walk

April 19, 2023

Quantum deep Q learning with distributed prioritized experience replay
Samuel Yen-Chi Chen
Quantum Physic Experience Replay Quantum Reinforcement Learning Asynchronous Training

March 29, 2023

Quantum Deep Hedging
El Amine Cherrat, Snehal Raj, Iordanis Kerenidis, Abhishek Shekhar, Ben Wood, Jon Dee, Shouvanik Chakrabarti, Richard Chen, Dylan Herman, Shaohan Hu, Pierre Minssen, Ruslan Shaydulin, Yue Sun, Romina Yalovetzky, Marco Pistoia
Deep Reinforcement Learning Quantum Machine Learning Quantum Physic Quantum Reinforcement Learning Quantum Model Deep Hedging

March 20, 2023

What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement
Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen
Neural Network Deep Learning Raw Data Quantum Physic Quantum Entanglement Local Self Attention Sufficient Condition

March 17, 2023

Hybrid Classic-Quantum Computing for Staging of Invasive Ductal Carcinoma of Breast
Vicente Moret-Bonillo, Eduardo Mosqueira-Rey, Samuel Magaz-Romero, Diego Alvarez-Estevez
Quantum Physic Efficient Hybrid Quantum Classical Light Stage Breast Tissue Quantum AI

March 16, 2023

Challenges and Opportunities in Quantum Machine Learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
Technical Challenge Quantum Machine Learning Emerging Opportunity Quantum Computing Quantum Physic Quantum Material

March 6, 2023

Parallel Hybrid Networks: an interplay between quantum and classical neural networks
Mo Kordzanganeh, Daria Kosichkina, Alexey Melnikov
Quantum Physic Variational Quantum Circuit Classical Neural Network Hybrid Quantum Parallel Hybrid Network

February 10, 2023

Effects of noise on the overparametrization of quantum neural networks
Diego García-Martín, Martin Larocca, M. Cerezo
Neural Network Mixed Effect Industrial Disturbing Noise Quantum Physic Quantum Neural Network Overparametrization Bound Parameterized Quantum Quantum Fisher Information

February 9, 2023

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems
Chanyoung Park, Won Joon Yun, Jae Pyoung Kim, Tiago Koketsu Rodrigues, Soohyun Park, Soyi Jung, Joongheon Kim
Multi Agent Reinforcement Learning Quantum Computing Quantum Physic Multiple Unmanned Aerial Vehicle Multi UAV Multi Agent Actor Critic Cooperative Communication

February 1, 2023

A supplemental investigation of non-linearity in quantum generative models with respect to simulatability and optimization
Kaitlin Gili, Rohan S. Kumar, Mykolas Sveistrys, C. J. Ballance
Generative Model Optimization Purpose Quantum Physic Quantum Circuit Quantum Algorithm Quantum Model Circuit Analysis Interpretability Scale Non Linearity Counterfactual Simulatability

January 31, 2023

Quantum contextual bandits and recommender systems for quantum data
Shrigyan Brahmachari, Josep Lumbreras, Marco Tomamichel
Recommender System Contextual Bandit Quantum Physic Contextual Linear Bandit Phase Recognition Unknown Quantum

January 23, 2023

Quantum Heavy-tailed Bandits
Yulian Wu, Chaowen Guan, Vaneet Aggarwal, Di Wang
Quantum Physic Heavy Tailed Quantum Reinforcement Learning Quantum Monte Carlo

January 17, 2023

The quantum cost function concentration dependency on the parametrization expressivity
Lucas Friedrich, Jonas Maziero
Quantum Computing Quantum Physic Variational Quantum Circuit Quantum Machine Learning Model Expressivity Transfer Noisy Intermediate Scale Quantum Device

January 12, 2023

On the explainability of quantum neural networks based on variational quantum circuits
Ammar Daskin
Neural Network High Explainability Quantum Physic Variational Quantum Circuit Ridge Function

January 9, 2023

VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum
Huanyu Bian, Zhilong Jia, Menghan Dou, Yuan Fang, Lei Li, Yiming Zhao, Hanchao Wang, Zhaohui Zhou, Wei Wang, Wenyu Zhu, Ye Li, Yang Yang, Weiming Zhang, Nenghai Yu, Zhaoyun Chen, Guoping Guo
Quantum Machine Learning Quantum Physic Quantum Processor Quantum Autoencoders

Quantum Physic

Papers

Trainability barriers and opportunities in quantum generative modeling

The cross-sectional stock return predictions via quantum neural network and tensor network

Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk

Quantum deep Q learning with distributed prioritized experience replay

Quantum Deep Hedging

A Framework for Demonstrating Practical Quantum Advantage: Racing Quantum against Classical Generative Models

Quantum Multi-Model Fitting

Quantum approximate optimization via learning-based adaptive optimization

What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement

Hybrid Classic-Quantum Computing for Staging of Invasive Ductal Carcinoma of Breast

Challenges and Opportunities in Quantum Machine Learning

Parallel Hybrid Networks: an interplay between quantum and classical neural networks

Effects of noise on the overparametrization of quantum neural networks

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems

A supplemental investigation of non-linearity in quantum generative models with respect to simulatability and optimization

Quantum contextual bandits and recommender systems for quantum data

Quantum Heavy-tailed Bandits

The quantum cost function concentration dependency on the parametrization expressivity

On the explainability of quantum neural networks based on variational quantum circuits

VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum