The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
<p dir="ltr">Recent advances in quantum computing and machine learning have brought about a promising intersection of these two fields, leading to the emergence of quantum machine learning (QML). However, the integration of quantum computing and machine learning poses several challen...
محفوظ في:
| المؤلف الرئيسي: | Muhammad Kashif (3923483) (author) |
|---|---|
| مؤلفون آخرون: | Saif Al-Kuwari (16904610) (author) |
| منشور في: |
2023
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Design Space Exploration of Hybrid Quantum–Classical Neural Networks
حسب: Muhammad Kashif (3923483)
منشور في: (2021) -
The impact of cost function globality and locality in hybrid quantum neural networks on NISQ devices
حسب: Muhammad Kashif (3923483)
منشور في: (2023) -
Generalized Remote Preparation of Arbitrary m-qubit Entangled States via Genuine Entanglements
حسب: Dong Wang (73290)
منشور في: (2015) -
ResQNets: a residual approach for mitigating barren plateaus in quantum neural networks
حسب: Muhammad Kashif (3923483)
منشور في: (2024) -
Physical Realization of Measurement Based Quantum Computation
حسب: Muhammad Kashif (3923483)
منشور في: (2023)