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qubo-nn
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| qsearch | qubo-nn | |
|---|---|---|
| 1 | 3 | |
| 27 | 40 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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Hardware vs Software
If you’d like to see my code, it’s on GitHub.
qubo-nn
- Reverse-Engineering QUBO Matrices
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How do you handle imbalanced datasets?
Here is an example.
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I accidentally tried to train 1 Quadrillion parameters - and a story of structural bias
In the course of that project (see here: https://github.com/instance01/qubo-nn) the second part turned out to be quite tough, likely due to the high dimensionality (4096 input size). In the post above I go through a mistake I made in which I assumed underfitting whereas in reality my data had structural bias (randomness that cannot be learnt by a neural network).
What are some alternatives?
quantum-benchmarks - benchmarking quantum circuit emulators for your daily research usage
Cirq - A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.
openqaoa - Multi-backend SDK for quantum optimisation
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
quantumcat - quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort.
quantum-nearest-classifier - Cirq implementation of Nearest Centroid Classification on a Trapped Ion Quantum Computer (Johri et al., 2020)
qBraid - A Python toolkit for cross-framework abstraction, transpilation, and execution of quantum programs.