17 citations · 22 across the 3 of their papers we have counts for
3 papers
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base
William W. Cohen, Haitian Sun, R. Alex Hofer +1
We describe a novel way of representing a symbolic knowledge base (KB) called a sparse-matrix reified KB. This representation enables neural modules that are fully differentiable,…
Differentiable Representations For Multihop Inference Rules
William W. Cohen, Haitian Sun, R. Alex Hofer +1
We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB). We introduce a new operation which can be used t…
Neural Query Language: A Knowledge Base Query Language for Tensorflow
William W. Cohen, Matthew Siegler, Alex Hofer
Large knowledge bases (KBs) are useful for many AI tasks, but are difficult to integrate into modern gradient-based learning systems. Here we describe a framework for accessing sof…