---
title: "Richard S. Zemel — all works — Elamur Research"
description: "All 215 works of Richard S. Zemel in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
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---
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# Richard S. Zemel — all works

215 works · page 1 of 3 · 1–100 · [← Richard S. Zemel](https://md.research.elamur.ai/free/en/authors/richard-s-zemel/)

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1. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention arXiv:1502.03044**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,670 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
2. **[Prototypical Networks for Few-shot Learning ↗](https://arxiv.org/abs/1703.05175) arXiv:1703.05175 · no summary yet**Jake Snell, Kevin Swersky, Richard S. Zemel*2017 · 5,249 citations*
3. **[Fairness through awareness ↗](https://doi.org/10.1145/2090236.2090255) no summary yet**Cynthia Dwork et al.*2012 · 3,499 citations*
4. **[Siamese Neural Networks for One-shot Image Recognition ↗](https://www.cs.toronto.edu/~rsalakhu/papers/oneshot1.pdf) ICML 2015 Deep Learning Workshop · no summary yet**Gregory Koch, Richard Zemel, Ruslan Salakhutdinov*2015 · 3,175 citations*
5. [**Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books arXiv:1506.06724**Yukun Zhu, Ryan Kiros, Richard Zemel, et al.*2015 · 3,083 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2015-aligning-books-movies-towards-story/)
6. **[Shortcut Learning in Deep Neural Networks ↗](https://doi.org/10.1038/s42256-020-00257-z) arXiv:2004.07780 · no summary yet**Robert Geirhos et al.*2020 · 2,366 citations*
7. **[Advances in Neural Information Processing Systems 5 ↗](https://openalex.org/W2598912124) no summary yet**Richard S. Zemel, Christopher K. I. Williams, Michael C. Mozer*1993 · 1,854 citations*
8. [**Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models arXiv:1411.2539**Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel*2014 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/kiros-2014-unifying-visual-semantic-embeddings-multimodal/)
9. **[Skip-Thought Vectors ↗](https://arxiv.org/abs/1506.06726) arXiv (Cornell University) · no summary yet**Ryan Kiros et al.*2015 · 1,267 citations*
10. **[The Helmholtz Machine ↗](https://doi.org/10.1162/neco.1995.7.5.889) Neural Computation · no summary yet**Peter Dayan et al.*1995 · 1,202 citations*
11. **[Autoencoders, Minimum Description Length and Helmholtz Free Energy ↗](https://openalex.org/W2102409316) no summary yet**Geoffrey E. Hinton, Richard S. Zemel*1993 · 1,073 citations*
12. **[Multiscale conditional random fields for image labeling ↗](https://doi.org/10.1109/cvpr.2004.1315232) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Xuming He, Richard S. Zemel, Miguel Á. Carreira-Perpiñán*2004 · 838 citations*
13. **[Understanding the Effective Receptive Field in Deep Convolutional Neural Networks ↗](https://arxiv.org/abs/1701.04128) arXiv (Cornell University) · no summary yet**Wenjie Luo et al.*2017 · 771 citations*
14. **[Information processing with population codes ↗](https://doi.org/10.1038/35039062) Nature reviews. Neuroscience · no summary yet**Alexandre Pouget, Peter Dayan, Richard S. Zemel*2000 · 753 citations*
15. **[Meta-Learning for Semi-Supervised Few-Shot Classification ↗](https://arxiv.org/abs/1803.00676) arXiv (Cornell University) · no summary yet**Mengye Ren et al.*2018 · 742 citations*
16. **[Gated Graph Sequence Neural Networks ↗](https://arxiv.org/abs/1511.05493) arXiv:1511.05493 · no summary yet**Yujia Li et al.*2015 · 576 citations*
17. **[Exploring Models and Data for Image Question Answering ↗](https://arxiv.org/abs/1505.02074) arXiv:1505.02074 · no summary yet**Mengye Ren, Ryan Kiros, Richard Zemel*2015 · 455 citations*
18. **[I NFERENCE AND C OMPUTATION WITH P OPULATION C ODES ↗](https://doi.org/10.1146/annurev.neuro.26.041002.131112) Annual Review of Neuroscience · no summary yet**Alexandre Pouget, Peter Dayan, Richard S. Zemel*2003 · 434 citations*
19. **[Probabilistic Interpretation of Population Codes ↗](https://doi.org/10.1162/089976698300017818) Neural Computation · no summary yet**Richard S. Zemel, Peter Dayan, Alexandre Pouget*1998 · 324 citations*
20. **[Collaborative prediction and ranking with non-random missing data ↗](https://doi.org/10.1145/1639714.1639717) ACM Conference on Recommender Systems (RecSys) · no summary yet**Benjamin M. Marlin, Richard S. Zemel*2009 · 317 citations*
21. **[End-to-End Instance Segmentation with Recurrent Attention ↗](https://doi.org/10.1109/cvpr.2017.39) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Mengye Ren, Richard S. Zemel*2017 · 305 citations*
22. **[Causal Effect Inference with Deep Latent-Variable Models ↗](https://arxiv.org/abs/1705.08821) UvA-DARE (University of Amsterdam) · no summary yet**Christos Louizos et al.*2017 · 290 citations*
23. **[Neural Relational Inference for Interacting Systems ↗](https://hdl.handle.net/11245.1/0f5e9586-b2ff-4344-a05b-a0d82ef41414) UvA-DARE (University of Amsterdam) · no summary yet**Thomas Kipf et al.*2018 · 281 citations*
24. **[Learning Adversarially Fair and Transferable Representations ↗](https://arxiv.org/abs/1802.06309) arXiv (Cornell University) · no summary yet**David Madras et al.*2018 · 204 citations*
25. **[Object-based attention and occlusion: Evidence from normal participants and a computational model. ↗](https://doi.org/10.1037//0096-1523.24.4.1011) Journal of Experimental Psychology Human Perception & Performance · no summary yet**Marlene Behrmann, Richard S. Zemel, Michael C. Mozer*1998 · 195 citations*
26. **[Collaborative Filtering and the Missing at Random Assumption ↗](https://arxiv.org/abs/1206.5267) arXiv (Cornell University) · no summary yet**Benjamin M. Marlin et al.*2012 · 180 citations*
27. **[Learning to generate images with perceptual similarity metrics ↗](https://doi.org/10.1109/icip.2017.8297089) Proceedings - International Conference on Image Processing · no summary yet**Jake Snell et al.*2015 · 179 citations*
28. **[Efficient Graph Generation with Graph Recurrent Attention Networks ↗](https://arxiv.org/abs/1910.00760) arXiv (Cornell University) · no summary yet**Renjie Liao et al.*2019 · 170 citations*
29. **[LanczosNet: Multi-Scale Deep Graph Convolutional Networks ↗](https://arxiv.org/abs/1901.01484) arXiv (Cornell University) · no summary yet**Renjie Liao et al.*2019 · 164 citations*
30. **[Understanding the Origins of Bias in Word Embeddings ↗](https://arxiv.org/abs/1810.03611) arXiv (Cornell University) · no summary yet**Marc-Etienne Brunet et al.*2018 · 145 citations*
31. **[Learning and Incorporating Top-Down Cues in Image Segmentation ↗](https://doi.org/10.1007/11744023_27) Lecture notes in computer science · no summary yet**Xuming He, Richard S. Zemel, Debajyoti Ray*2006 · 138 citations*
32. **[Flexibly Fair Representation Learning by Disentanglement ↗](https://arxiv.org/abs/1906.02589) arXiv (Cornell University) · no summary yet**Elliot Creager et al.*2019 · 117 citations*
33. **[Proximity Graphs for Clustering and Manifold Learning ↗](https://openalex.org/W2163097311) neural information processing systems · no summary yet**Richard S. Zemel, Miguel Á. Carreira-Perpiñán*2004 · 116 citations*
34. **[HOP-MAP: Efficient Message Passing with High Order Potentials ↗](https://openalex.org/W2144414892) International Conference on Artificial Intelligence and Statistics · no summary yet**Daniel Tarlow, Inmar E. Givoni, Richard S. Zemel*2010 · 114 citations*
35. **[The Toronto Paper Matching System: An automated paper-reviewer assignment system ↗](https://openalex.org/W2155203104) no summary yet**Laurent Charlin, Richard S. Zemel*2013 · 108 citations*
36. **[Fairness through Causal Awareness ↗](https://doi.org/10.1145/3287560.3287564) no summary yet**David Madras et al.*2019 · 107 citations*
37. **[BoltzRank ↗](https://doi.org/10.1145/1553374.1553513) International Conference on Machine Learning · no summary yet**Maksims Volkovs, Richard S. Zemel*2009 · 103 citations*
38. **[Experience-dependent perceptual grouping and object-based attention. ↗](https://doi.org/10.1037/0096-1523.28.1.202) Journal of Experimental Psychology Human Perception & Performance · no summary yet**Richard S. Zemel et al.*2002 · 101 citations*
39. **[Deep Spectral Clustering Learning. ↗](https://openalex.org/W2740643007) International Conference on Machine Learning · no summary yet**Marc T. Law, Raquel Urtasun, Richard S. Zemel*2017 · 100 citations*
40. **[A Gradient-Based Boosting Algorithm for Regression Problems ↗](https://openalex.org/W2100559472) no summary yet**Richard S. Zemel, Toniann Pitassi*2000 · 100 citations*
41. **[A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex ↗](https://doi.org/10.1523/jneurosci.18-01-00531.1998) Journal of Neuroscience · no summary yet**Richard S. Zemel, Terrence J. Sejnowski*1998 · 98 citations*
42. **[A minimum description length framework for unsupervised learning ↗](https://openalex.org/W1578739277) no summary yet**Richard S. Zemel*1994 · 95 citations*
43. **[Proceedings of the 23rd International Conference on Neural Information Processing Systems ↗](https://openalex.org/W2914020154) no summary yet**John Lafferty et al.*2010 · 87 citations*
44. **[Ranking via Sinkhorn Propagation ↗](https://arxiv.org/abs/1106.1925) arXiv (Cornell University) · no summary yet**Ryan Prescott Adams, Richard S. Zemel*2011 · 86 citations*
45. **[Learning Deep Parsimonious Representations ↗](https://openalex.org/W2560977758) neural information processing systems · no summary yet**Renjie Liao et al.*2016 · 83 citations*
46. **[Competition and Multiple Cause Models ↗](https://doi.org/10.1162/neco.1995.7.3.565) Neural Computation · no summary yet**Peter Dayan, Richard S. Zemel*1995 · 83 citations*
47. **[Learning to Segment Images Using Dynamic Feature Binding ↗](https://doi.org/10.1162/neco.1992.4.5.650) Neural Computation · no summary yet**Michael C. Mozer et al.*1992 · 83 citations*
48. **[Inference in Probabilistic Graphical Models by Graph Neural Networks ↗](https://doi.org/10.1109/ieeeconf44664.2019.9048920) 2018 52nd Asilomar Conference on Signals, Systems, and Computers · no summary yet**Kijung Yoon et al.*2018 · 82 citations*
49. **[Few-Shot Learning Through an Information Retrieval Lens ↗](https://arxiv.org/abs/1707.02610) arXiv (Cornell University) · no summary yet**Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun*2017 · 81 citations*
50. **[“I’m fully who I am”: Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation ↗](https://doi.org/10.1145/3593013.3594078) ACM Conference on Fairness, Accountability, and Transparency (FAccT) · no summary yet**Anaelia Ovalle et al.*2023 · 79 citations*
51. **[The Elephant in the Room ↗](https://doi.org/10.13140/rg.2.2.15295.20642) arXiv (Cornell University) · no summary yet**Amir Rosenfeld, Richard S. Zemel, John K. Tsotsos*2018 · 76 citations*
52. **[Learning Latent Subspaces in Variational Autoencoders ↗](https://arxiv.org/abs/1812.06190) arXiv (Cornell University) · no summary yet**Jack Klys, Jake Snell, Richard S. Zemel*2018 · 72 citations*
53. **[Lending direction to neural networks ↗](https://doi.org/10.1016/0893-6080(94)00094-3) Neural Networks · no summary yet**Richard S. Zemel, Christopher K. I. Williams, Michael C. Mozer*1995 · 72 citations*
54. **[Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes ↗](https://arxiv.org/abs/1611.04520) arXiv (Cornell University) · no summary yet**Mengye Ren et al.*2016 · 71 citations*
55. **[Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data ↗](https://arxiv.org/abs/2006.10833) Data Archiving and Networked Services (DANS) · no summary yet**Sindy Löwe et al.*2020 · 70 citations*
56. **[Training Deep Neural Networks via Direct Loss Minimization ↗](https://arxiv.org/abs/1511.06411) arXiv (Cornell University) · no summary yet**Yang Song et al.*2015 · 69 citations*
57. **[Generative versus discriminative training of RBMs for classification of fMRI images ↗](https://openalex.org/W2162747531) no summary yet**Tanya Schmah et al.*2008 · 69 citations*
58. **[Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer ↗](https://arxiv.org/abs/1711.06664) arXiv (Cornell University) · no summary yet**David Madras, Toniann Pitassi, Richard S. Zemel*2017 · 68 citations*
59. **[Recommender systems: missing data and statistical model estimation ↗](https://doi.org/10.5591/978-1-57735-516-8/ijcai11-447) no summary yet**Benjamin M. Marlin et al.*2011 · 66 citations*
60. **[Excessive Invariance Causes Adversarial Vulnerability ↗](https://arxiv.org/abs/1811.00401) arXiv (Cornell University) · no summary yet**Jörn-Henrik Jacobsen et al.*2018 · 65 citations*
61. **[Environment Inference for Invariant Learning ↗](https://arxiv.org/abs/2010.07249) arXiv (Cornell University) · no summary yet**Elliot Creager, Joern-Henrik Jacobsen, Richard S. Zemel*2020 · 63 citations*
62. **[Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models ↗](https://arxiv.org/abs/1906.09427) arXiv (Cornell University) · no summary yet**Guangyong Chen et al.*2019 · 55 citations*
63. **[Graph Partition Neural Networks for Semi-Supervised Classification ↗](https://arxiv.org/abs/1803.06272) arXiv (Cornell University) · no summary yet**Renjie Liao et al.*2018 · 55 citations*
64. **[Learning Articulated Structure and Motion ↗](https://doi.org/10.1007/s11263-010-0325-y) International Journal of Computer Vision · no summary yet**David A. Ross, Daniel Tarlow, Richard S. Zemel*2010 · 49 citations*
65. **[Automated detection of unusual events on stairs ↗](https://doi.org/10.1016/j.imavis.2008.04.021) Image and Vision Computing · no summary yet**Jasper Snoek et al.*2008 · 49 citations*
66. **[Learning Population Codes by Minimizing Description Length ↗](https://doi.org/10.1162/neco.1995.7.3.549) Neural Computation · no summary yet**Richard S. Zemel, Geoffrey E. Hinton*1995 · 48 citations*
67. **[A flexible generative model for preference aggregation ↗](https://doi.org/10.1145/2187836.2187902) International World Wide Web Conference (WWW) · no summary yet**Maksims Volkovs, Richard S. Zemel*2012 · 46 citations*
68. **[Lorentzian Distance Learning for Hyperbolic Representations ↗](https://openalex.org/W2955067198) International Conference on Machine Learning · no summary yet**Marc T. Law et al.*2019 · 45 citations*
69. **[Structured Output Learning with High Order Loss Functions ↗](https://openalex.org/W2182705849) no summary yet**Daniel Tarlow, Richard S. Zemel*2012 · 45 citations*
70. **[Proceedings of the 23rd International Conference on Neural Information Processing Systems - Volume 1 ↗](https://openalex.org/W2912280546) no summary yet**John Lafferty et al.*2010 · 45 citations*
71. **[A Multiplicative Model for Learning Distributed Text-Based Attribute Representations ↗](https://arxiv.org/abs/1406.2710) arXiv (Cornell University) · no summary yet**Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov*2014 · 44 citations*
72. **[Collaborative Ranking With 17 Parameters ↗](https://openalex.org/W2101101192) no summary yet**Maksims Volkovs, Richard S. Zemel*2012 · 44 citations*
73. **[FLIRT: Feedback Loop In-context Red Teaming](https://md.research.elamur.ai/free/en/papers/mehrabi-2024-flirt-feedback-loop-context-red/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, et al.*2024 · 42 citations*
74. **[Comparing Classification Methods for Longitudinal fMRI Studies ↗](https://doi.org/10.1162/neco_a_00024) Neural Computation · no summary yet**Tanya Schmah et al.*2010 · 40 citations*
75. **[Learning Hybrid Models for Image Annotation with Partially Labeled Data ↗](https://openalex.org/W2151862441) no summary yet**Xuming He, Richard S. Zemel*2008 · 40 citations*
76. **[A Neural Autoregressive Approach to Attention-based Recognition ↗](https://doi.org/10.1007/s11263-014-0765-x) International Journal of Computer Vision · no summary yet**Yin Zheng et al.*2014 · 36 citations*
77. **[Differentially Private Decoding in Large Language Models ↗](https://arxiv.org/abs/2205.13621) arXiv (Cornell University) · no summary yet**Jimit Majmudar et al.*2022 · 35 citations*
78. **[New learning methods for supervised and unsupervised preference aggregation ↗](https://doi.org/10.5555/2627435.2638572) no summary yet**Maksims Volkovs, Richard S. Zemel*2014 · 35 citations*
79. **[Self Supervised Boosting ↗](https://openalex.org/W2103504567) no summary yet**Max Welling, Richard S. Zemel, Geoffrey E. Hinton*2002 · 35 citations*
80. **[Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic](https://md.research.elamur.ai/free/en/papers/camara-2022-mapping-multilingual-margins-intersectional-biases/) [Workshop on Language Technology for Equality, Diversity, Inclusion](https://md.research.elamur.ai/free/en/venues/ltedi/)**António Câmara, Nina Taneja, Tamjeed Azad, et al.*2022 · 33 citations*
81. **[Reviving and Improving Recurrent Back-Propagation ↗](https://arxiv.org/abs/1803.06396) arXiv (Cornell University) · no summary yet**Renjie Liao et al.*2018 · 33 citations*
82. **[Incremental Few-Shot Learning with Attention Attractor Networks ↗](https://arxiv.org/abs/1810.07218) arXiv (Cornell University) · no summary yet**Mengye Ren et al.*2018 · 33 citations*
83. **[Exploring Compositional High Order Pattern Potentials for Structured Output Learning ↗](https://doi.org/10.1109/cvpr.2013.14) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Yujia Li, Daniel Tarlow, Richard S. Zemel*2013 · 33 citations*
84. **[A Framework for Optimizing Paper Matching ↗](https://arxiv.org/abs/1202.3706) arXiv (Cornell University) · no summary yet**Laurent Charlin, Richard S. Zemel, Craig E. Boutilier*2012 · 33 citations*
85. **[Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling ↗](https://arxiv.org/abs/2002.05616) arXiv (Cornell University) · no summary yet**Will Grathwohl et al.*2020 · 32 citations*
86. **[Localist Attractor Networks ↗](https://doi.org/10.1162/08997660151134325) Neural Computation · no summary yet**Richard S. Zemel, Michael C. Mozer*2001 · 30 citations*
87. **[Discovering Viewpoint-Invariant Relationships That Characterize Objects ↗](https://openalex.org/W2142150270) no summary yet**Richard S. Zemel, Geoffrey E. Hinton*1990 · 30 citations*
88. **[Variational Model Inversion Attacks ↗](https://arxiv.org/abs/2201.10787) arXiv (Cornell University) · no summary yet**Kuan-Chieh Wang et al.*2022 · 29 citations*
89. **[Adversarial Distillation of Bayesian Neural Network Posteriors ↗](https://arxiv.org/abs/1806.10317) arXiv (Cornell University) · no summary yet**Kuan-Chieh Wang et al.*2018 · 29 citations*
90. **[Active Collaborative Filtering ↗](https://arxiv.org/abs/1212.2442) arXiv (Cornell University) · no summary yet**Craig E. Boutilier, Richard S. Zemel, Benjamin M. Marlin*2012 · 29 citations*
91. **[A Divergence Minimization Perspective on Imitation Learning Methods ↗](https://arxiv.org/abs/1911.02256) arXiv (Cornell University) · no summary yet**Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel, Shixiang Gu*2019 · 28 citations*
92. **[On the Representational Efficiency of Restricted Boltzmann Machines ↗](https://openalex.org/W2126229007) no summary yet**James Martens et al.*2013 · 27 citations*
93. **[Fast Exact Inference for Recursive Cardinality Models ↗](https://arxiv.org/abs/1210.4899) arXiv (Cornell University) · no summary yet**Daniel Tarlow et al.*2012 · 27 citations*
94. **[Encoding and Decoding Spikes for Dynamic Stimuli ↗](https://doi.org/10.1162/neco.2008.01-07-436) Neural Computation · no summary yet**Rama D Natarajan et al.*2008 · 27 citations*
95. **[Multiple Cause Vector Quantization ↗](https://openalex.org/W2103521987) no summary yet**David A. Ross, Richard S. Zemel*2002 · 26 citations*
96. **[Toward Informal Language Processing: Knowledge of Slang in Large Language Models ↗](https://aclanthology.org/2024.naacl-long.94/) Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yet**Zhewei Sun et al.*2024 · 25 citations*
97. **[Learning to rank by aggregating expert preferences ↗](https://doi.org/10.1145/2396761.2396868) ACM International Conference on Information and Knowledge Management (CIKM) · no summary yet**Maksims Volkovs, Hugo Larochelle, Richard S. Zemel*2012 · 25 citations*
98. **[Mean-Field Networks ↗](https://arxiv.org/abs/1410.5884) arXiv (Cornell University) · no summary yet**Yujia Li, Richard S. Zemel*2014 · 23 citations*
99. **[Topological map learning from outdoor image sequences ↗](https://doi.org/10.1002/rob.20170) Journal of Field Robotics · no summary yet**Xuming He, Richard S. Zemel, Volodymyr Mnih*2006 · 23 citations*
100. **[Advances in Neural Information Processing Systems 21 ↗](https://openalex.org/W2598141122) no summary yet**Rama D Natarajan et al.*2009 · 22 citations*

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