2 papers
quant-ph2019
Improved Boltzmann machines with error corrected quantum annealing
Richard Y. Li, Tameem Albash, Daniel A. Lidar
Boltzmann machines are the basis of several deep learning methods that have been successfully applied to both supervised and unsupervised machine learning tasks. These models assum…
quant-ph2018
Quantum annealing versus classical machine learning applied to a simplified computational biology problem
Richard Y. Li, Rosa Di Felice, Remo Rohs +1
Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective…