183 citations · 474 across the 24 of their papers we have counts for
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Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss
Vedant Shah, Aditya Agrawal, Lovekesh Vig +3
We are interested in neurosymbolic systems consisting of a high-level symbolic layer for explainable prediction in terms of human-intelligible concepts; and a low-level neural laye…
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
Vishwa Shah, Aditya Sharma, Gautam Shroff +3
Analogical Reasoning problems challenge both connectionist and symbolic AI systems as these entail a combination of background knowledge, reasoning and pattern recognition. While s…
Composition of Relational Features with an Application to Explaining Black-Box Predictors
Ashwin Srinivasan, A Baskar, Tirtharaj Dash +1
Relational machine learning programs like those developed in Inductive Logic Programming (ILP) offer several advantages: (1) The ability to model complex relationships amongst data…
One-way Explainability Isn't The Message
Ashwin Srinivasan, Michael Bain, Enrico Coiera
Recent engineering developments in specialised computational hardware, data-acquisition and storage technology have seen the emergence of Machine Learning (ML) as a powerful form o…