Code for the ICLR 2024 paper "How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data"
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Updated
Feb 2, 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]
A list of awesome resources related to constraint learning
A dedicated repository for learning and researching about neuro-symbolic artificial intelligence (NSAI)
Coursework for COMSE6998 Natural Language Generation and Summarization
AI UK Fringe Event on AI research at City, University of London
The repository is to document neurosymbolic AI architectures
Personal website of Ernesto Jiménez-Ruiz, Lecturer in AI at City, University of London
Endless conversations between GPT and Google Gemini with possible human interaction
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