Exploring the applications of deep reinforcement learning and quantum variational circuit In quantum machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
Auteurs principaux: | Saha, Prashanta Kumar, Saha, Vishal |
---|---|
Autres auteurs: | Upoma, Ipshita Bonhi |
Format: | Thèse |
Langue: | English |
Publié: |
Brac University
2021
|
Sujets: | |
Accès en ligne: | http://hdl.handle.net/10361/15680 |
Documents similaires
-
Quantum error correction using quantum convolutional neural network
par: Mishu, Niloy Deb Roy, et autres
Publié: (2021) -
Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
par: Ahmed, Sajjad
Publié: (2019) -
Reinforcement learning based autonomous vehicle for exploration and exploitation of undiscovered track
par: Issa, Razin Bin, et autres
Publié: (2020) -
Enhancing object clarity in single channel night vision images using deep reinforcement learning
par: Hossain, Adil, et autres
Publié: (2021) -
The Mathematical language of Quantum Theory
par: Teiko Heinosaari, Mário Ziman
Publié: (2012)