With the rapid development of quantum computers, a number of quantum algorithms have been developed and tested on both superconducting qubits based machines and ion trap hardware. Quantum machine learning is expected to be a potential application of quantum computer in the near future. Many quantum machine learning algorithms have been proposed to speed up classical machine learning by quantum computers. At the same time, deep learning has shown great power in solving real world problems. The aim of the workshop is to bring together world leading experts in this new field of quantum machine learning to discuss the recent development of quantum algorithms to perform machine learning tasks on large-scale scientific datasets for various industrial and technological applications and in solving challenging problems in science and engineering.

Agenda (subject to change)

Day #1:  Thursday, September 5th

7:00 - 8:00 a.m.                            Registration & Breakfast

8:00 - 8:15 a.m.                            Welcome Remarks 

Morning Session:                         Hosted by Oak Ridge National Laboratories:  Travis Humble
8:15 - 9:15 a.m.                            Universal Variational Quantum Computation
                                                     Jacob Biamonte, Skolkovo Institute
9:15 - 10:00 a.m.                          Quantum Machine Learning & the Prospect of Near-Term Application on Noisy Devices
                                                      Kristan Temme, IBM
10:00 10:30 a.m.                           Coffee Break
10:30 - 11:15 a.m.                         Training Quantum Boltzmann Machines
                                                      Nathan Weibe, University of Washington
11:15 - 12:00 p.m.                          Quantum Boltzmann Machine Using Eigenstate Thermalization
                                                       Yudong Cao, Zapata
12:00 - 1:30 p.m.                            Lunch

Afternoon Session:                         Hosted by Entanglement Institute, Jason Turner
1:30 - 2:15 p.m.                              Training with Gradient Estimation on NISQ Devices for Quantum Machine Learning Applications
                                                       Kathleen Hamilton, Oak Ridge National Laboratories
2:15 - 3:00 p.m.                              Supervised Quantum Machine Learning with Photonic Qudits
                                                        Stephen Gray, ANL
3:00 - 3:30 p.m.                              Coffee Break
3:30 - 4:15 p.m.                               Coupled Cluster Downfolding Techniques for Quantum Computing:  Dimensionality Reduction of Electronic Hamiltonians in Studies of Correlated Molecular Systems
                                                        Karol Kowalski
4:15 - 5:00 p.m.                               Case Studies in Machine Learning Via Quantum Annealing
                                                        Richard Li, USC
5:30 - 9:00 p.m.                              Dinner for invited speakers

Day #2:  Friday, September 6th
7:00 - 8:00 a.m.                              Breakfast

Morning Session:                           Alex Pothen, Purdue
8:00 - 8:15 a.m.                              Integrative Data Science Initiative
                                                      Sunil Prabhakar, Purdue
8:15 - 8:30 a.m.                              Purdue Quantum Science and Engineering Institute 
                                                       Yong Chen, Purdue
8:30 - 9:30 a.m.                              Challenges and opportunities for hybrid quantum-classical machine learning and optimization
                                                        Masoud Mohseni, Google
9:30 - 10:15 a.m.                             TBA
                                                        Chad Rigetti, Rigetti Computing
10:15 - 10:45 a.m.                           Coffee Break
10:45 - 11:30 a.m.                           Machine Leanring for Quantum Control
                                                        Barry Sanders, University of Calgary
11:30 - 12:15 p.m.                           Penny Lane - AUtomatic Differentiation and Machine Learning of Quantum Computations
                                                        Nathan Kiloran, Xanadu
12:15 - 1:30 p.m.                             Lunch

Afternoon Session:  Ashraf Alam, Purdue
1:30 - 2:15 p.m.                               Quantum Computing and Artificial Intelligence
                                                         Antonio Mezzacapo, IBM
2:15 - 3:00 p.m.                               Quantum Algorithms for Systems of LInear Equations
                                                        Rolando Somma, LANL
3:00 - 3:15 p.m.                               Coffee Break
3:15 - 4:00 p.m.                               p-Bits for Quantum-inspired Algorithms
                                                        Supriyo Datta, Purdue
4:00 - 4:15 p.m.                               Closing Remarks
                                                        Sabre Kais, Purdue

Register to attend by August 15th.