19 citations · 47 across the 3 of their papers we have counts for
5 papers
Mathematical Reasoning in Latent Space
Dennis Lee, Christian Szegedy, Markus N. Rabe +2
We design and conduct a simple experiment to study whether neural networks can perform several steps of approximate reasoning in a fixed dimensional latent space. The set of rewrit…
Learning to Reason in Large Theories without Imitation
Kshitij Bansal, Christian Szegedy, Markus N. Rabe +2
In this paper, we demonstrate how to do automated theorem proving in the presence of a large knowledge base of potential premises without learning from human proofs. We suggest an…
Graph Representations for Higher-Order Logic and Theorem Proving
Aditya Paliwal, Sarah Loos, Markus Rabe +2
This paper presents the first use of graph neural networks (GNNs) for higher-order proof search and demonstrates that GNNs can improve upon state-of-the-art results in this domain.…
HOList: An Environment for Machine Learning of Higher-Order Theorem Proving
Kshitij Bansal, Sarah M. Loos, Markus N. Rabe +2
We present an environment, benchmark, and deep learning driven automated theorem prover for higher-order logic. Higher-order interactive theorem provers enable the formalization of…
Deep Network Guided Proof Search
Sarah Loos, Geoffrey Irving, Christian Szegedy +1
Deep learning techniques lie at the heart of several significant AI advances in recent years including object recognition and detection, image captioning, machine translation, spee…