QuantumAI-IITM
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DA6300-2025
DA6300-2025 PublicContent related to the Jan-May 2025 session of the course DA6300: Quantum Computing and Machine Learning
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Automated-Discovery-and-Optimization-of-Quantum-Error-Correction-Codes-Using-ML
Automated-Discovery-and-Optimization-of-Quantum-Error-Correction-Codes-Using-ML PublicJupyter Notebook
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qiskit-ML-workspace
qiskit-ML-workspace PublicForked from qiskit-community/qiskit-machine-learning
A dataset generation framework for Qiskit Machine Learning, similar to Iris/MNIST in classical ML, is being developed by this group (Shailesh ME22B192, Nishant ME21B132, Rishi EE21B111). These data…
Python
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Quantum-Circuit-Optimization-using-AlphaTensorQuantum
Quantum-Circuit-Optimization-using-AlphaTensorQuantum PublicIn NISQ era, quantum circuit depths are very crucial for quantum computational advantage. The most expensive gates in terms of T1 decoherence time are the Non-Clifford gates, especially the T-gate.…
Jupyter Notebook
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Repositories
- qiskit-ML-workspace Public Forked from qiskit-community/qiskit-machine-learning
A dataset generation framework for Qiskit Machine Learning, similar to Iris/MNIST in classical ML, is being developed by this group (Shailesh ME22B192, Nishant ME21B132, Rishi EE21B111). These datasets will benchmark QNNs and VQAs against classical methods to demonstrate quantum advantage.
- Enhanced-Classification-of-Class-Imbalanced-Datasets-using-Hybrid-Quantum-Models Public
This project explores hybrid quantum-classical models for enhanced classification of class-imbalanced datasets. It implements Hybrid Quantum Neural Networks (HQNNs) and quantum-enhanced algorithms (Random Forest, KNN, SVM) to improve minority class prediction.
- Quantum-Circuit-Optimization-using-AlphaTensorQuantum Public
In NISQ era, quantum circuit depths are very crucial for quantum computational advantage. The most expensive gates in terms of T1 decoherence time are the Non-Clifford gates, especially the T-gate. This work is an attempt to optimize the quantum circuit depth by minimizing the number of T-gates in any circuit using Deep Reinforcement Learning.
- GQE_For_Drug_Prediction Public
- Quantum_Tangent_Kernel Public
- DA6300-2025 Public
Content related to the Jan-May 2025 session of the course DA6300: Quantum Computing and Machine Learning
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