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.
Główni autorzy: | Saha, Prashanta Kumar, Saha, Vishal |
---|---|
Kolejni autorzy: | Upoma, Ipshita Bonhi |
Format: | Praca dyplomowa |
Język: | English |
Wydane: |
Brac University
2021
|
Hasła przedmiotowe: | |
Dostęp online: | http://hdl.handle.net/10361/15680 |
Podobne zapisy
-
Quantum error correction using quantum convolutional neural network
od: Mishu, Niloy Deb Roy, i wsp.
Wydane: (2021) -
Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
od: Ahmed, Sajjad
Wydane: (2019) -
Reinforcement learning based autonomous vehicle for exploration and exploitation of undiscovered track
od: Issa, Razin Bin, i wsp.
Wydane: (2020) -
Enhancing object clarity in single channel night vision images using deep reinforcement learning
od: Hossain, Adil, i wsp.
Wydane: (2021) -
The Mathematical language of Quantum Theory
od: Teiko Heinosaari, Mário Ziman
Wydane: (2012)