Code for the ICLR 2024 paper "How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data"
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Updated
Aug 27, 2024 - Python
Code for the ICLR 2024 paper "How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data"
Learning for planning architecture using both classical and deep learning methods. [AAAI-24, ICAPS-24]
Code and data of "NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems"
headquarters of the April team in Edinburgh
A list of awesome resources related to constraint learning
A dedicated repository for learning and researching about neuro-symbolic artificial intelligence (NSAI)
LLY-HDC uses hyperdimesnional computing and neurosymbolic AI to implement a high-performance AI model on quantum computers
AI UK Fringe Event on AI research at City, University of London
Coursework for COMSE6998 Natural Language Generation and Summarization
Personal website of Ernesto Jiménez-Ruiz, Lecturer in AI at City, University of London
An LLM-based code translator for whole-program translation, fine-tuned using feedback from compiler and symbolic execution
Endless conversations between GPT and Google Gemini with possible human interaction
The repository is to document neurosymbolic AI architectures
Headquarters of the APRIL research lab
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