| Gated Graph Sequence Neural Networks Y Li, D Tarlow, M Brockschmidt, R Zemel International Conference on Learning Representations (ICLR), 2016 | 3542 | 2016 |
| Learning to Represent Programs with Graphs M Allamanis, M Brockschmidt, M Khademi International Conference on Learning Representations (ICLR), 2018 | 858 | 2018 |
| CodeSearchNet Challenge: Evaluating the State of Semantic Code Search H Husain, HH Wu, T Gazit, M Allamanis, M Brockschmidt arXiv preprint arXiv:1909.09436, 2019 | 670 | 2019 |
| DeepCoder: Learning to Write Programs M Balog, AL Gaunt, M Brockschmidt, S Nowozin, D Tarlow International Conference on Learning Representations (ICLR), 2017 | 642 | 2017 |
| Constrained Graph Variational Autoencoders for Molecule Design Q Liu, M Allamanis, M Brockschmidt, AL Gaunt Conference on Neural Information Processing Systems (NeurIPS), 2018 | 452 | 2018 |
| Structured Neural Summarization P Fernandes, M Allamanis, M Brockschmidt International Conference on Learning Representations (ICLR), 2019 | 227 | 2019 |
| Generative Code Modeling with Graphs M Brockschmidt, M Allamanis, AL Gaunt, O Polozov International Conference on Learning Representations (ICLR), 2019 | 171 | 2019 |
| Analyzing program termination and complexity automatically with AProVE J Giesl, C Aschermann, M Brockschmidt, F Emmes, F Frohn, C Fuhs, ... Journal of Automated Reasoning 58 (1), 3-31, 2017 | 159 | 2017 |
| Proving termination of programs automatically with AProVE J Giesl, M Brockschmidt, F Emmes, F Frohn, C Fuhs, C Otto, M Plücker, ... International Joint Conference on Automated Reasoning (IJCAR), 184 - 191, 2014 | 125 | 2014 |
| TerpreT: A Probabilistic Programming Language for Program Induction AL Gaunt, M Brockschmidt, R Singh, N Kushman, P Kohli, J Taylor, ... arXiv preprint arXiv:1608.04428, 2016 | 123 | 2016 |
| Learning to Represent Edits P Yin, G Neubig, M Allamanis, M Brockschmidt, AL Gaunt International Conference on Learning Representations (ICLR), 2019 | 108 | 2019 |
| GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation M Brockschmidt International Conference on Machine Learning (ICML), 2020 | 106 | 2020 |
| Automated termination analysis of Java Bytecode by term rewriting C Otto, M Brockschmidt, C Von Essen, J Giesl Rewriting Techniques and Applications (RTA), 259-276, 2010 | 103 | 2010 |
| Better termination proving through cooperation M Brockschmidt, B Cook, C Fuhs International Conference on Computer Aided Verification (CAV), 413-429, 2013 | 99 | 2013 |
| Robust text-to-sql generation with execution-guided decoding C Wang, K Tatwawadi, M Brockschmidt, PS Huang, Y Mao, O Polozov, ... arXiv preprint arXiv:1807.03100, 2018 | 93 | 2018 |
| Alternating runtime and size complexity analysis of integer programs M Brockschmidt, F Emmes, S Falke, C Fuhs, J Giesl Tools and Algorithms for the Construction and Analysis of Systems (TACAS …, 2014 | 91 | 2014 |
| Analyzing Information Leakage of Updates to Natural Language Models S Zanella-Béguelin, L Wutschitz, S Tople, V Rühle, A Paverd, ... Computer and Communications Security (CCS), 2020 | 90 | 2020 |
| Self-Supervised Bug Detection and Repair M Allamanis, H Jackson-Flux, M Brockschmidt Neural Information Processing Systems (NeurIPS), 2021 | 86 | 2021 |
| Analyzing runtime and size complexity of integer programs M Brockschmidt, F Emmes, S Falke, C Fuhs, J Giesl ACM Transactions on Programming Languages and Systems (TOPLAS) 38 (4), 1-50, 2016 | 83 | 2016 |
| Graph Partition Neural Networks for Semi-Supervised Classification R Liao, M Brockschmidt, D Tarlow, A Gaunt, R Urtasun, R Zemel International Conference on Learning Representations [Workshop Track] (ICLR), 2018 | 79 | 2018 |
Daniel TarlowResearch Scientist, Google Brain - MontrealVerified email at cs.toronto.edu
