1. Learning to optimize halide with tree search and random programs
2. Miltiadis Allamanis Marc Brockschmidt and Mahmoud Khademi. 2017. Learning to Represent Programs with Graphs. arxiv:1711.00740 [cs.LG] Miltiadis Allamanis Marc Brockschmidt and Mahmoud Khademi. 2017. Learning to Represent Programs with Graphs. arxiv:1711.00740 [cs.LG]
3. Uri Alon , Shaked Brody , Omer Levy , and Eran Yahav . 2018. code2seq: Generating Sequences from Structured Representations of Code. arXiv: Learning ( 2018 ). Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav. 2018. code2seq: Generating Sequences from Structured Representations of Code. arXiv: Learning (2018).
4. Avishkar Bhoopchand Tim Rocktäschel Earl Barr and Sebastian Riedel. 2016. Learning Python Code Suggestion with a Sparse Pointer Network. (2016). http://arxiv.org/abs/1611.08307 Avishkar Bhoopchand Tim Rocktäschel Earl Barr and Sebastian Riedel. 2016. Learning Python Code Suggestion with a Sparse Pointer Network. (2016). http://arxiv.org/abs/1611.08307
5. Tianqi Chen , Lianmin Zheng , Eddie Yan , Ziheng Jiang , Thierry Moreau , Luis Ceze , Carlos Guestrin , and Arvind Krishnamurthy . 2018. Learning to optimize tensor programs. Advances in Neural Information Processing Systems 31 ( 2018 ). Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy. 2018. Learning to optimize tensor programs. Advances in Neural Information Processing Systems 31 (2018).