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Sarah M. Loos | Christian Szegedy | Markus N. Rabe | Aditya Paliwal | Kshitij Bansal | Sarah Loos | Markus Rabe | Christian Szegedy | Aditya Sanjay Paliwal | Kshitij Bansal
[1] Boris Polyak,et al. Acceleration of stochastic approximation by averaging , 1992 .
[2] John Harrison,et al. HOL Light: A Tutorial Introduction , 1996, FMCAD.
[3] Katrin Baumgartner. Logic for Programming, Artificial Intelligence, and Reasoning , 2003, Lecture Notes in Computer Science.
[4] Gregory N. Hullender,et al. Learning to rank using gradient descent , 2005, ICML.
[5] Georges Gonthier,et al. Formal Proof—The Four- Color Theorem , 2008 .
[6] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[7] Jeremy Avigad,et al. A Machine-Checked Proof of the Odd Order Theorem , 2013, ITP.
[8] Cezary Kaliszyk,et al. Learning-Assisted Automated Reasoning with Flyspeck , 2012, Journal of Automated Reasoning.
[9] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[10] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[11] Razvan Pascanu,et al. A simple neural network module for relational reasoning , 2017, NIPS.
[12] Jian Wang,et al. Premise Selection for Theorem Proving by Deep Graph Embedding , 2017, NIPS.
[13] Razvan Pascanu,et al. Discovering objects and their relations from entangled scene representations , 2017, ICLR.
[14] Cyrus Shahabi,et al. Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting , 2017, ArXiv.
[15] Elad Eban,et al. Scalable Learning of Non-Decomposable Objectives , 2016, AISTATS.
[16] Thibault Gauthier,et al. TacticToe: Learning to Reason with HOL4 Tactics , 2017, LPAR.
[17] Tobias Nipkow,et al. A FORMAL PROOF OF THE KEPLER CONJECTURE , 2015, Forum of Mathematics, Pi.
[18] Samuel S. Schoenholz,et al. Neural Message Passing for Quantum Chemistry , 2017, ICML.
[19] Cezary Kaliszyk,et al. Deep Network Guided Proof Search , 2017, LPAR.
[20] Razvan Pascanu,et al. Relational inductive biases, deep learning, and graph networks , 2018, ArXiv.
[21] Sanjit A. Seshia,et al. Learning Heuristics for Automated Reasoning through Deep Reinforcement Learning , 2018, ArXiv.
[22] Cyrus Shahabi,et al. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting , 2017, ICLR.
[23] Simon Cruanes,et al. Superposition for Lambda-Free Higher-Order Logic , 2018, IJCAR.
[24] Richard Evans,et al. Can Neural Networks Understand Logical Entailment? , 2018, ICLR.
[25] Chong Wang,et al. Neural Logic Machines , 2019, ICLR.
[26] Jure Leskovec,et al. How Powerful are Graph Neural Networks? , 2018, ICLR.
[27] Dawn Xiaodong Song,et al. GamePad: A Learning Environment for Theorem Proving , 2018, ICLR.
[28] Nikolaj Bjørner,et al. Guiding High-Performance SAT Solvers with Unsat-Core Predictions , 2019, SAT.
[29] Sarah M. Loos,et al. HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving , 2019, ICML.
[30] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[31] Sarah M. Loos,et al. HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version) , 2019, ArXiv.
[32] Jia Deng,et al. Learning to Prove Theorems via Interacting with Proof Assistants , 2019, ICML.
[33] Sorin Lerner,et al. Generating correctness proofs with neural networks , 2019, MAPL@PLDI.
[34] Edward A. Lee,et al. Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning , 2018, ICLR.