Parsing with Compositional Vector Grammars
Richard Socher, John Bauer, Christopher D. Manning and Andrew Y. Ng
Association for Computational Linguistics 2013 Conference (ACL 2013)
[ paper, project page: full training and testing code, bibtex, etc.]

Better Word Representations with Recursive Neural Networks for Morphology
Thang Luong, Richard Socher, Christopher D. Manning
Conference on Computational Natural Language Learning (CoNLL 2013)

Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors
Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Y. Ng
International Conference on Learning Representations (ICLR 2013, Workshop Track)
[ paper ]

Zero-Shot Learning Through Cross-Modal Transfer
Richard Socher, Milind Ganjoo, Hamsa Sridhar, Osbert Bastani, Christopher D. Manning, Andrew Y. Ng
International Conference on Learning Representations (ICLR 2013, Workshop Track, Oral)
[ paper ]

Convolutional-Recursive Deep Learning for 3D Object Classification
Richard Socher, Brody Huval, Bharath Bhat, Christopher D. Manning and Andrew Y. Ng
Advances in Neural Information Processing Systems (NIPS 2012)
[ paper, project page: full training and testing code, bibtex, etc.]

Semantic Compositionality through Recursive Matrix-Vector Spaces
Richard Socher, Brody Huval, Christopher D. Manning and Andrew Y. Ng
Conference on Empirical Methods in Natural Language Processing (EMNLP 2012, Oral)
[ paper, project page: full training and testing code, dataset, bibtex, etc.]

Improving Word Representations via Global Context and Multiple Word Prototypes
Eric H. Huang, Richard Socher, Christopher D. Manning and Andrew Y. Ng
Association for Computational Linguistics 2012 Conference (ACL 2012)
[ paper, project page: code, word vectors, dataset, bibtex, etc. ]

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
Richard Socher, Eric H. Huang, Jeffrey Pennington, Andrew Y. Ng, and Christopher D. Manning
Advances in Neural Information Processing Systems (NIPS 2011)
[ paper, project page: test code for full paraphrase detection, data, bibtex, etc. ]

Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
Richard Socher, Jeffrey Pennington, Eric Huang, Andrew Y. Ng, and Christopher D. Manning
Conference on Empirical Methods in Natural Language Processing (EMNLP 2011, Oral)
[ paper, project page: train+test code, EP dataset, bibtex, etc. ]

Parsing Natural Scenes and Natural Language with Recursive Neural Networks
Richard Socher, Cliff Lin, Andrew Y. Ng, and Christopher D. Manning
The 28th International Conference on Machine Learning (ICML 2011)
Distinguished Application Paper Award
[ paper, project page: train+test code, data, bibtex, etc., video ]

Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities
Richard Socher, Andrew Maas, Christopher D. Manning
Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011)
[ paper, project page ]

Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks
Richard Socher, Christopher D. Manning, Andrew Y. Ng
Deep Learning and Unsupervised Feature Learning Workshop - NIPS 2010, Oral
[ paper (added details on 3/3/2012) ]

A Gibbs Sampler for Spatial Clustering with the Distance-dependent Chinese Restaurant Process
Richard Socher and Christopher D. Manning
Monte Carlo Methods for Modern Applications Workshop - NIPS 2010
[ paper ]

Connecting Modalities: Semi-supervised Segmentation and Annotation of Images Using Unaligned Text Corpora
Richard Socher and Li Fei-Fei
IEEE Computer Vision and Pattern Recognition (CVPR 2010)
[ paper, code+data, project page ]

A Bayesian analysis of dynamics in free recall
Richard Socher, Sam J. Gershman, Adler Perotte, Per Sederberg, Ken A. Norman, and David M. Blei
Advances in Neural Information Processing Systems 22 (NIPS 2009)
[ paper, code+data, poster, project page ]

Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework
Li-Jia Li, Richard Socher, and Li Fei-Fei
IEEE Computer Vision and Pattern Recognition (CVPR 2009, Oral)
[ paper, code+data, slides, project page ]

ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei
IEEE Computer Vision and Pattern Recognition (CVPR 2009)
[ paper, project page ]

A Learning Based Hierarchical Model for Vessel Segmentation
Richard Socher, Adrian Barbu, and Dorin Comaniciu
In 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2008, Oral)
[ paper, slides, project page ]

Combining Contexts in Lexicon Learning for Semantic Parsing
Richard Socher, Chris Biemann, and Rainer Osswald
Proceedings of NODALIDA 2007, Tartu, Estonia
[ paper, slides, bibtex ]