16 citations · 43 across the 7 of their papers we have counts for
8 papers
A Review of Uncertainty for Deep Reinforcement Learning
Owen Lockwood, Mei Si
Uncertainty is ubiquitous in games, both in the agents playing games and often in the games themselves. Working with uncertainty is therefore an important component of successful d…
An Empirical Review of Optimization Techniques for Quantum Variational Circuits
Owen Lockwood
Quantum Variational Circuits (QVCs) are often claimed as one of the most potent uses of both near term and long term quantum hardware. The standard approaches to optimizing these c…
QuantumCircuitOpt: An Open-source Framework for Provably Optimal Quantum Circuit Design
Harsha Nagarajan, Owen Lockwood, Carleton Coffrin
In recent years, the quantum computing community has seen an explosion of novel methods to implement non-trivial quantum computations on near-term hardware. An important direction…
Optimizing Quantum Variational Circuits with Deep Reinforcement Learning
Owen Lockwood
Quantum Machine Learning (QML) is considered to be one of the most promising applications of near term quantum devices. However, the optimization of quantum machine learning models…
Playing Atari with Hybrid Quantum-Classical Reinforcement Learning
Owen Lockwood, Mei Si
Despite the successes of recent works in quantum reinforcement learning, there are still severe limitations on its applications due to the challenge of encoding large observation s…
In Defense of the Paper
Owen Lockwood
The machine learning publication process is broken, of that there can be no doubt. Many of these flaws are attributed to the current workflow: LaTeX to PDF to reviewers to camera r…
Reinforcement Learning with Quantum Variational Circuits
Owen Lockwood, Mei Si
The development of quantum computational techniques has advanced greatly in recent years, parallel to the advancements in techniques for deep reinforcement learning. This work expl…
TensorFlow Quantum: A Software Framework for Quantum Machine Learning
Michael Broughton, Guillaume Verdon, Trevor McCourt +26
We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high…