nlp:neurosymbolic_methods
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Table of Contents
Neurosymbolic Methods
Overviews
- See related work (section 2) of Wu 2020
- Tutorials
Papers
- Evans & Grefenstette 2017 - Learning Explanatory Rules from Noisy Data Introduces Differentiable Inductive Logic Programming, which is trained using backpropagation. DILP provides “data efficiency and generalisation beyond what neural networks can achieve on their own.”
- Wang et al 2019 - Evidence Sentence Extraction for Machine Reading Comprehension Uses Deep Probabilistic Logic
- Wu et al 2020 - Deep Weighted MaxSAT for Aspect-based Opinion Extraction See the related work
People
Related Pages
nlp/neurosymbolic_methods.1745024930.txt.gz · Last modified: 2025/04/19 01:08 by jmflanig