GA + LLM hybrid framework for structured text generation and task optimization.
A modular toolkit for designing, analyzing, and validating hybrid AI systems using Boxology visual patterns.
A hybrid AI model for predicting failures in water distribution systems using Adaptive Neuro-Fuzzy Inference System (ANFIS). The model integrates Genetic Algorithms (GA) and Ant Colony Optimization (ACO) to improve the accuracy of accident prediction.
Гибридная модель ИИ для автошахмат, сочетающая формальные эвристики и адаптивное поведение.
Quantum Natural Language Processing (QNLP) using Quantum LSTM (QLSTM) architectures for advanced text classification tasks. This project demonstrates how quantum-inspired LSTM networks can be applied to natural language understanding and classification using Qiskit/PennyLane.
textual entailment experiments on Mednli dataset.
HAL, the Hybrid Artificial-Intelligence Layer, is the future of artificial intelligence. It's a layered approach that combines different AI techniques to create a more complex and adaptable system. HAL's layers work together to gather data from the environment, interpret it, learn from it, and make informed decisions based on that knowledge.
SymRAG adaptively routes queries through neuro-symbolic, neural, or hybrid paths based on complexity and system load, ensuring efficient and accurate RAG for diverse QA tasks.
Hybrid classical-quantum system for gas leak detection and drone path planning using synthetic GPLA-12 data, classical ML, and quantum-inspired optimization.
Hybrid GNN-SNN AI model for early Parkinson's disease detection using spiking neurons and graph learning
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