121 citations · 271 across the 9 of their papers we have counts for
10 papers
Proving Theorems using Incremental Learning and Hindsight Experience Replay
Eser Aygün, Laurent Orseau, Ankit Anand +5
Traditional automated theorem provers for first-order logic depend on speed-optimized search and many handcrafted heuristics that are designed to work best over a wide range of dom…
Training a First-Order Theorem Prover from Synthetic Data
Vlad Firoiu, Eser Aygun, Ankit Anand +6
A major challenge in applying machine learning to automated theorem proving is the scarcity of training data, which is a key ingredient in training successful deep learning models.…
Learning to Prove from Synthetic Theorems
Eser Aygün, Zafarali Ahmed, Ankit Anand +5
A major challenge in applying machine learning to automated theorem proving is the scarcity of training data, which is a key ingredient in training successful deep learning models.…
Early Visual Concept Learning with Unsupervised Deep Learning
Irina Higgins, Loic Matthey, Xavier Glorot +5
Automated discovery of early visual concepts from raw image data is a major open challenge in AI research. Addressing this problem, we propose an unsupervised approach for learning…
Theano: A Python framework for fast computation of mathematical expressions
The Theano Development Team, Rami Al-Rfou, Guillaume Alain +110
Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has bee…
A Semantic Matching Energy Function for Learning with Multi-relational Data
Xavier Glorot, Antoine Bordes, Jason Weston +1
Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or i…