| Rectifier nonlinearities improve neural network acoustic models AL Maas, AY Hannun, AY Ng Proc. icml 30 (1), 3, 2013 | 9717 | 2013 |
| Learning word vectors for sentiment analysis A Maas, RE Daly, PT Pham, D Huang, AY Ng, C Potts Proceedings of the 49th annual meeting of the association for computational …, 2011 | 6146 | 2011 |
| Maximum entropy inverse reinforcement learning. BD Ziebart, AL Maas, JA Bagnell, AK Dey Aaai 8, 1433-1438, 2008 | 3589 | 2008 |
| Recurrent neural networks for noise reduction in robust asr. AL Maas, QV Le, TM O'Neil, O Vinyals, P Nguyen, AY Ng Interspeech 2012, 22-25, 2012 | 431 | 2012 |
| Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior BD Ziebart, AL Maas, AK Dey, JA Bagnell Proceedings of the 10th international conference on Ubiquitous computing …, 2008 | 400 | 2008 |
| First-pass large vocabulary continuous speech recognition using bi-directional recurrent DNNs AY Hannun, AL Maas, D Jurafsky, AY Ng arXiv preprint arXiv:1408.2873, 2014 | 215 | 2014 |
| Lexicon-Free Conversational Speech Recognition with Neural Networks AL Maas, Z Xie, D Jurafsky, AY Ng North American Chapter of the Association for Computational Linguistics (NAACL), 2015 | 192 | 2015 |
| Building DNN acoustic models for large vocabulary speech recognition AL Maas, P Qi, Z Xie, AY Hannun, CT Lengerich, D Jurafsky, AY Ng Computer Speech & Language 41, 195-213, 2017 | 189 | 2017 |
| Methods, apparatus and systems for annotation of text documents C Potts, E Lin, A Maas, A Itharaju, K Reschke, J Vincent US Patent 11,263,391, 2022 | 110 | 2022 |
| Human Behavior Modeling with Maximum Entropy Inverse Optimal Control. BD Ziebart, AL Maas, JA Bagnell, AK Dey AAAI spring symposium: human behavior modeling 92, 2009 | 82 | 2009 |
| A probabilistic model for semantic word vectors AL Maas, AY Ng NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 1-8, 2010 | 70 | 2010 |
| Offering verified credentials in massive open online courses: Moocs and technology to advance learning and learning research (ubiquity symposium) A Maas, C Heather, C Do, R Brandman, D Koller, A Ng Ubiquity 2014 (May), 1-11, 2014 | 63* | 2014 |
| Spectral chinese restaurant processes: Nonparametric clustering based on similarities R Socher, A Maas, C Manning Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 54 | 2011 |
| Word-level acoustic modeling with convolutional vector regression AL Maas, SD Miller, TM O’neil, AY Ng, P Nguyen Proc. ICML Workshop Representation Learn, 2012 | 41 | 2012 |
| Retrofitting distributional embeddings to knowledge graphs with functional relations BJ Lengerich, AL Maas, C Potts arXiv preprint arXiv:1708.00112, 2017 | 37 | 2017 |
| Sentiment expression conditioned by affective transitions and social forces M Sudhof, A Goméz Emilsson, AL Maas, C Potts Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 36 | 2014 |
| Unsupervised feature learning and deep learning A Ng, J Ngiam, CY Foo, Y Mai, C Suen, A Coates, A Maas, A Hannun, ... Technical report, Stanford University, 2013 | 31 | 2013 |
| Recurrent neural network feature enhancement: The 2nd CHiME challenge AL Maas, TM O’Neil, AY Hannun, AY Ng Proceedings The 2nd CHiME Workshop on Machine Listening in Multisource …, 2013 | 29 | 2013 |
| Sequence to sequence transformations for speech synthesis via recurrent neural networks DLW Hall, D Klein, D Roth, L Gillick, A Maas, S Wegmann US Patent App. 15/792,236, 2018 | 25 | 2018 |
| One-shot learning with bayesian networks A Maas, C Kemp Carnegie Mellon University, 2009 | 21 | 2009 |
Christopher PottsProfessor of Linguistics and, by courtesy, of Computer ScienceVerifierad e-postadress på stanford.edu
