44 citations · 88 across the 6 of their papers we have counts for
5 papers · 1 filter
Learning to Prepare Molecular Ground States with Transformer Models
Alex Koziell-Pipe, Jasmine Brewer, Jem Guhit +14
Quantum state preparation is a key component of many quantum algorithms. Performing this step efficiently is essential for realizing practical quantum advantage in quantum chemistr…
QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits
Ilya Tyagin, Marwa H. Farag, Kyle Sherbert +3
Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algori…
A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation
Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +4
The success of the self-attention mechanism in classical machine learning models has inspired the development of quantum analogs aimed at reducing computational overhead. Self-atte…
Artificial Intelligence for Quantum Computing
Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries
Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +8
The nexus of quantum computing and machine learning - quantum machine learning - offers the potential for significant advancements in chemistry. This review specifically explores t…