qiskit-symb
pennylane
qiskit-symb | pennylane | |
---|---|---|
1 | 3 | |
22 | 2,124 | |
- | 1.9% | |
7.2 | 9.8 | |
3 months ago | 5 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
qiskit-symb
pennylane
- PennyLane: Python library for differentiable programming of quantum computers
-
Library for Machine learning and quantum computing
Pennylane
- pennylane: PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network
What are some alternatives?
devito - DSL and compiler framework for automated finite-differences and stencil computation
qiskit-ibm-provider - Qiskit Provider for accessing the IBM Quantum Services: Online Systems and Simulators
qiskit - Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
ADCME.jl - Automatic Differentiation Library for Computational and Mathematical Engineering
qBraid - A Python toolkit for cross-framework abstraction, transpilation, and execution of quantum programs.
Cirq - A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.
machine_learning_refined - Notes, examples, and Python demos for the 2nd edition of the textbook "Machine Learning Refined" (published by Cambridge University Press).
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
foolbox - A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
ivy - The Unified Machine Learning Framework [Moved to: https://github.com/unifyai/ivy]
qiskit-ibm-runtime - IBM Client for Qiskit Runtime
jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.