Neuro Symbolic Reasoning Resource Page

This page is designed to provide resources on Neuro Symbolic Reasoning.

Our associated YouTube channel: https://www.youtube.com/channel/UC3fICY_FqiUnnjgQZyN1AjQ

Other associated NSR pages:
https://people.cs.ksu.edu/~hitzler/nesy/
https://www.city-data-science-institute.com/nesy
https://sites.google.com/view/nsptutorial

Here we provides sides and tutorials on several notable NSR papers – we have created this as part of a course, so more to come soon.

Here we provides sides and tutorials on several notable NSR papers – we have created this as part of a course, so more to come soon.

• Introductory and Review material
  • Kautz’s taxonomy: Slides, Paper (Kautz), Paper (“3rd Wave”)
  • Shortcomings of the current state-of-the-art: Slides, Paper (Marcus, 2018)
  • NSR Framework  overview: Slides
  • Review of propositional logic and FOL: Slides
  • Review of PGM’s (MRF, MLN, PSL):  Slides
• Frameworks where the logic program is known a-priori
  • Logical Neural Networks:  Slides, Paper, 4-Part Video series in a YouTube playlist 
    • Training LNN’s (based on Lu et al.’s 2021 paper): slides
  • Logic Tensor Networks Slides, Paper, 3-Part Video series in a YouTube playlist
  • NeurASP  paper, YouTube video series
    • Follow-on work: SLASH  (Slides, paper, paper)
    • Info on the ASP language
  • NeuPSL: Slides, Paper, PSL/NeuPSL video series
• NSR and Inductive Logic Programming (ILP)
  • Differentiable ILP:  Original  framework  of  Evans  and  Grefenstette  (Slides, Paper)
  • Extension for structured examples by Shindo et al. (Slides, Paper)
  • Extension for LNN (Slides, Paper)
• NSR and Ontological Reasoning
  • Deep Ontological Networks: Slides, Paper
  • Deep Deductive Reasoning for Cross-KG Entailment Slides, paper
• Other NSR topics
  • NSR and verification
    • STL Net: slides, paper, supplement
    • Perception logic: paper
  • Constraint learning and symbol grounding: SATNet  Slides
    • 3-Part Video series in a YouTube playlist: https://www.youtube.com/watch?v=IsDpoXExmNA&list=PLpqh-PUKX-i5F6w73sEnZBKQu1QAItYSj
    • Papers featured in the video and slides: SATNet, SATNet and Symbol Grounding #1, SATNet and Symbol Grounding #2
    • Further reading: general info on symbol grounding, alternative approach to constraint learning
  • Neural approaches to symbolic regression
    • Deep Symbolic Regression: Slides (also covers Transformer approach and DSP), DSR paper
    • Transformer-based SR: paper
    • DSP: paper
  • Datasets: CLEVERER (paper)

Contributors
Paulo Shakarian, Associate Professor, Arizona State University
Gerardo I. Simari, Assistant Professor, Universidad Nacional del Sur (Argentina)
Chitta Baral, Professor, Arizona State University
Rohan Reddy Sambidi, ASU
Yao Ting Chen, ASU
Joshua Noronha, ASU
Yamil Soto, UNS (Argentina)
Damián Furman, UNS (Argentina)
Stephanie Malvicini, UNS (Argentina)
Zhung Yang, ASU
John Cava, ASU
Joshua Elkins, ASU
Sahil Patel, ASU