QTML 2023: 7TH INTERNATIONAL CONFERENCE ON QUANTUM TECHINQUES IN MACHINE LEARNING
PROGRAM FOR FRIDAY, NOVEMBER 24TH
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09:00-10:45 Session 27: Gradients and Landscape Theory
09:00
Adrián Pérez-Salinas, Hao Wang and Xavier Bonet-Monroig
Analyzing variational quantum landscapes with information content
09:15
Martin Larocca, Marco Cerezo, Sujay Kazi, Patrick Coles, Marco Farinati and Robert Zeier
The landscape of QAOA Max-Cut Lie algebras
09:30
Julian Berberich, Daniel Fink, Daniel Pranjic, Christian Tutschku and Christian Holm
Training robust quantum classifiers based on Lipschitz bounds
10:00
Amira Abbas, Robbie King, Hsin-Yuan Huang, William J Huggins, Ramis Movassagh, Dar Gilboa and Jarrod McClean
On quantum backpropagation, information reuse, and cheating measurement collapse
10:30
Roeland Wiersema, Dylan Lewis, David Wierichs, Nathan Killoran and Juan Carrasquilla
Here comes the SU(N) multivariate quantum gates and gradients
10:45-11:15Coffee Break
11:15-12:00 Session 28: INVITED TALK: Clemens Gneiting. Approximate Autonomous Quantum Error Correction with Reinforcement Learning

Approximate Autonomous Quantum Error Correction with Reinforcement Learning

12:00-13:15 Session 29: Reinforcement Learning and Robust Learning
12:00
Thomas Elliott, Mile Gu, Andrew Garner and Jayne Thompson
Quantum adaptive agents with efficient long-term memories
12:30
Friederike Metz and Marin Bukov
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
12:45
Maxwell West, Chris Nakhl, Jamie Heredge, Floyd Creevey, Christopher Leckie, Sarah Erfani, Lloyd Hollenberg, Martin Sevior and Muhammad Usman
Quantum machine learning with enhanced adversarial robustness
13:00
Debbie Huey Chih Lim, João F. Doriguello and Patrick Rebentrost
Quantum algorithm for robust optimization via stochastic-gradient online learning
13:15-14:45Lunch Break
14:45-15:30 Session 30: Quantum Monte Carlo
14:45
Jinzhao Sun, Yukun Zhang, Xiao Yuan, Dingshun Lv and Yifei Huang
Quantum Computing Quantum Monte Carlo
15:15
Koichi Miyamoto
Quantum Metropolis-Hastings algorithm with the target distribution calculated by quantum Monte Carlo integration
15:30-16:15 Session 31: Quantum Optimization
15:30
Akshay Vishwanathan, Daniil Rabinovich, Ernesto Campos and Jacob Biamonte
On The Performance And Limitation Of Quantum Approximate Optimization
15:45
Pietro Torta, Guglielmo Lami, Juan Carrasquilla, Mario Collura and Estelle Inack
Quantum optimization of Binary Neural Networks
16:00
Kostas Blekos, Dean Brand, Andrea Ceschini, Chiao-Hui Chou, Rui-Hao Li, Komal Pandya and Alessandro Summer
Performance Analysis and Comparative Study of Quantum Approximate Optimization Algorithm Variants
16:15-17:00 Session 32: Quantum Reservoir Computing
16:15
Filip Wudarski, Daniel O'Connor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, Aaron Lott and Davide Venturelli
Hybrid quantum-classical reservoir computing for solving chaotic systems
16:30
Apimuk Sornsaeng, Ninnat Dangniam and Thiparat Chotibut
Next Generation Quantum Reservoir Computing: An Efficient Quantum Algorithm for Forecasting Quantum Dynamics
16:45
Pere Mujal, Rodrigo Martínez-Peña, Gian Luca Giorgi, Miguel C. Soriano and Roberta Zambrini
Time-series quantum reservoir computing with weak and projective measurements