| Structured Denoising Diffusion Models in Discrete State-Spaces J Austin, D Johnson, J Ho, D Tarlow, R Berg Advances in Neural Information Processing Systems, 2021, 2021 | 457 | 2021 |
| Generating Polyphonic Music Using Tied Parallel Networks DD Johnson International Conference on Evolutionary and Biologically Inspired Music and …, 2017 | 136 | 2017 |
| Learning Graphical State Transitions DD Johnson International Conference on Learning Representations, 2017 | 117* | 2017 |
| Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming A Paszke, DD Johnson, D Duvenaud, D Vytiniotis, A Radul, MJ Johnson, ... Proceedings of the ACM on Programming Languages 5 (ICFP), 1-29, 2021 | 42 | 2021 |
| Learning to Create Jazz Melodies Using a Product of Experts DD Johnson, RM Keller, N Weintraut Eighth International Conference on Computational Creativity, ICCC, Atlanta, 2017, 0 | 27* | |
| Learning Graph Structure With A Finite-State Automaton Layer DD Johnson, H Larochelle, D Tarlow Advances in Neural Information Processing Systems 33, 2020 | 19 | 2020 |
| Contrastive learning can find an optimal basis for approximately view-invariant functions DD Johnson, A El Hanchi, CJ Maddison The Eleventh International Conference on Learning Representations, 2022 | 17 | 2022 |
| Learning Generalized Gumbel-max Causal Mechanisms G Lorberbom, DD Johnson, CJ Maddison, D Tarlow, T Hazan Advances in Neural Information Processing Systems 34, 26792-26803, 2021 | 16 | 2021 |
| Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models DD Johnson, J Austin, R van den Berg, D Tarlow ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | 16 | 2021 |
| RU-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents DD Johnson, D Tarlow, C Walder arXiv preprint arXiv:2303.00732, 2023 | 3 | 2023 |
| A Library for Representing Python Programs as Graphs for Machine Learning D Bieber, K Shi, P Maniatis, C Sutton, V Hellendoorn, D Johnson, ... arXiv preprint arXiv:2208.07461, 2022 | 3 | 2022 |
| Latent Gaussian Activity Propagation: Using Smoothness and Structure to Separate and Localize Sounds in Large Noisy Environments D Johnson, D Gorelik, RE Mawhorter, K Suver, W Gu, S Xing, C Gabriel, ... Advances in Neural Information Processing Systems, 3465-3474, 2018 | 2 | 2018 |
| Parallel Algebraic Effect Handlers N Xie, DD Johnson, D Maclaurin, A Paszke arXiv preprint arXiv:2110.07493, 2021 | 1 | 2021 |
| LEG processor for education M Waugaman, Z Davidson, S Dietrich, D Johnson, C Meyer, E Storm, ... 2016 11th European Workshop on Microelectronics Education (EWME), 1-5, 2016 | 1 | 2016 |
| Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs DD Johnson, D Tarlow, D Duvenaud, CJ Maddison arXiv preprint arXiv:2402.08733, 2024 | | 2024 |
| Machine-Learned Models for Generating Code Snippets with Predicted Placeholders for Optimizing Software Development DDW Johnson, DS Tarlow, M Tabachnyk, MH Rasi, J Austin, ... US Patent App. 17/832,199, 2023 | | 2023 |
| A density estimation perspective on learning from pairwise human preferences V Dumoulin, DD Johnson, PS Castro, H Larochelle, Y Dauphin arXiv preprint arXiv:2311.14115, 2023 | | 2023 |
| Geometric Realizations of the 3D Associahedron (Multimedia Exposition) SL Devadoss, DD Johnson, J Lee, J Warley 34th International Symposium on Computational Geometry (SoCG 2018), 2018 | | 2018 |
Daniel TarlowResearch Scientist, Google DeepMind - MontrealVerified email at cs.toronto.edu
