3 citations · 8 across the 5 of their papers we have counts for
10 papers
Bayesian Experimental Design for Symbolic Discovery
Kenneth L. Clarkson, Cristina Cornelio, Sanjeeb Dash +3
This study concerns the formulation and application of Bayesian optimal experimental design to symbolic discovery, which is the inference from observational data of predictive mode…
Learning to Guide a Saturation-Based Theorem Prover
Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni +8
Traditional automated theorem provers have relied on manually tuned heuristics to guide how they perform proof search. Recently, however, there has been a surge of interest in the…
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27
Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…
Symbolic Regression using Mixed-Integer Nonlinear Optimization
Vernon Austel, Cristina Cornelio, Sanjeeb Dash +4
The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of…
Schemaless Queries over Document Tables with Dependencies
Mustafa Canim, Cristina Cornelio, Arun Iyengar +2
Unstructured enterprise data such as reports, manuals and guidelines often contain tables. The traditional way of integrating data from these tables is through a two-step process o…
Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling
Maxwell Crouse, Ibrahim Abdelaziz, Cristina Cornelio +4
Recent advances in the integration of deep learning with automated theorem proving have centered around the representation of logical formulae as inputs to deep learning systems. I…