| Ask the GRU Multi-task Learning for Deep Text Recommendations T Bansal, D Belanger, A McCallum proceedings of the 10th ACM Conference on Recommender Systems, 107-114, 2016 | 215 | 2016 |
| Fast and accurate entity recognition with iterated dilated convolutions E Strubell, P Verga, D Belanger, A McCallum arXiv preprint arXiv:1702.02098, 2017 | 200 | 2017 |
| Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, Part 2: Nonplanar faults EM Dunham, D Belanger, L Cong, JE Kozdon Bulletin of the Seismological Society of America 101 (5), 2308-2322, 2011 | 173 | 2011 |
| Chains of reasoning over entities, relations, and text using recurrent neural networks R Das, A Neelakantan, D Belanger, A McCallum arXiv preprint arXiv:1607.01426, 2016 | 158 | 2016 |
| Structured prediction energy networks D Belanger, A McCallum International Conference on Machine Learning, 983-992, 2016 | 148 | 2016 |
| Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, Part 1: Planar faults EM Dunham, D Belanger, L Cong, JE Kozdon Bulletin of the Seismological Society of America 101 (5), 2296-2307, 2011 | 124 | 2011 |
| Sequential regulatory activity prediction across chromosomes with convolutional neural networks DR Kelley, YA Reshef, M Bileschi, D Belanger, CY McLean, J Snoek Genome research 28 (5), 739-750, 2018 | 113 | 2018 |
| End-to-end learning for structured prediction energy networks D Belanger, B Yang, A McCallum International Conference on Machine Learning, 429-439, 2017 | 90 | 2017 |
| Synthesizing normalized faces from facial identity features F Cole, D Belanger, D Krishnan, A Sarna, I Mosseri, WT Freeman Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 82 | 2017 |
| Multilingual relation extraction using compositional universal schema P Verga, D Belanger, E Strubell, B Roth, A McCallum arXiv preprint arXiv:1511.06396, 2015 | 82 | 2015 |
| Learning latent permutations with gumbel-sinkhorn networks G Mena, D Belanger, S Linderman, J Snoek arXiv preprint arXiv:1802.08665, 2018 | 77 | 2018 |
| Fast and Accurate Sequence Labeling with Iterated Dilated Convolutions. E Strubell, P Verga, D Belanger, A McCallum | 34 | 2017 |
| A linear dynamical system model for text D Belanger, S Kakade International Conference on Machine Learning, 833-842, 2015 | 33 | 2015 |
| Rapid prediction of electron–ionization mass spectrometry using neural networks JN Wei, D Belanger, RP Adams, D Sculley ACS central science 5 (4), 700-708, 2019 | 31 | 2019 |
| Implicit causal models for genome-wide association studies D Tran, DM Blei arXiv preprint arXiv:1710.10742, 2017 | 26 | 2017 |
| Marginal inference in mrfs using frank-wolfe D Belanger, D Sheldon, A McCallum NIPS Workshop on Greedy Optimization, Frank-Wolfe and Friends, 2013 | 24 | 2013 |
| Bethe projections for non-local inference L Vilnis, D Belanger, D Sheldon, A McCallum arXiv preprint arXiv:1503.01397, 2015 | 21 | 2015 |
| Model-based reinforcement learning for biological sequence design C Angermueller, D Dohan, D Belanger, R Deshpande, K Murphy, ... International Conference on Learning Representations, 2019 | 19 | 2019 |
| Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches. B Roth, N Monath, D Belanger, E Strubell, P Verga, A McCallum TAC, 2015 | 19 | 2015 |
| Using deep learning to annotate the protein universe ML Bileschi, D Belanger, D Bryant, T Sanderson, B Carter, D Sculley, ... bioRxiv, 626507, 2019 | 18 | 2019 |
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
