A project for meta-learning experiments
Project description
Krishna Bajpai Meta-Learn
[](https://github.com/yourorg/Krishna Bajpai-metalearn/actions)
A revolutionary meta-learning framework combining quantum-inspired optimization, neuromorphic computing, and evolutionary task dynamics for unparalleled adaptive AI capabilities.
Features
- 🌀 Quantum-Informed Meta-Optimization
- 🧠 Neuromorphic Architecture with spiking neural dynamics
- 🌌 4D Hypernetwork parameter generation
- 🧬 Evolutionary Task Environments with genetic programming
- ⚡ Hybrid Quantum-Classical computation support
Quick Start
from Krishna Bajpai import QuantumMetaLearner, NeuromorphicTransformer
# Initialize quantum-inspired meta-learner
model = NeuromorphicTransformer(input_dim=256)
learner = QuantumMetaLearner(model)
# Evolve tasks with genetic programming
tasks = evolve_task_population(base_tasks)
# Meta-train with hybrid optimization
learner.hybrid_train(tasks, qpu_backend='ionq_harmony')
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