Zemel, Richard

Fairness through awareness

Dwork, C., Hardt, M., Pitassi, T., Reingold, O., & Zemel, R. (2012) · Proceedings of the 3rd Innovations in Theoretical Computer Science Conference

Ethics and Social Impacts of AIPrivacy-Preserving Technologies in Data

Cited by 3,501

Shortcut learning in deep neural networks

Geirhos, R., Jacobsen, J.-H., Michaelis, C., Zemel, R., Brendel, W., Bethge, M., & Wichmann, F. A. (2020) · Nature Machine Intelligence

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 2,224

Understanding the Effective Receptive Field in Deep Convolutional Neural Networks

Luo, W., Li, Y., Urtasun, R., & Zemel, R. (2017) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 1,575

Skip-Thought Vectors

Kiros, R., Zhu, Y., Salakhutdinov, R., Zemel, R. S., Torralba, A., Urtasun, R., & Fidler, S. (2015) · arXiv

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 1,293

The helmholtz machine

Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995) · Neural Computation

Neural Networks and ApplicationsBayesian Modeling and Causal Inference

Cited by 1,207

Probabilistic Interpretation of Population Codes

Zemel, R. S., Dayan, P., & Pouget, A. (1998) · Neural Computation

Neural dynamics and brain functionMemory and Neural Mechanisms

Cited by 333

End-to-End Instance Segmentation with Recurrent Attention

Ren, M., & Zemel, R. S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 309

Learning to generate images with perceptual similarity metrics

Snell, J., Ridgeway, K., Liao, R., Roads, B. D., Mozer, M. C., & Zemel, R. S. (2017) · 2017 IEEE International Conference on Image Processing (ICIP)

Generative Adversarial Networks and Image SynthesisImage and Video Quality Assessment

Cited by 186

Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

Madras, D., Pitassi, T., & Zemel, R. (2017) · arXiv

Ethics and Social Impacts of AIMachine Learning and Algorithms

Cited by 90

“I’m fully who I am”: Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation

Ovalle, A., Goyal, P., Dhamala, J., Jaggers, Z., Chang, K.-W., Galstyan, A., Zemel, R., & Gupta, R. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AILGBTQ Health, Identity, and Policy

Cited by 43

Privacy in the Time of Language Models

Peris, C., Dupuy, C., Majmudar, J., Parikh, R., Smaili, S., Zemel, R., & Gupta, R. (2023) · Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 41

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions

Snell, J. C., Zollo, T. P., Deng, Z., Pitassi, T., & Zemel, R. (2022) · arXiv

Machine Learning and Data ClassificationRisk and Portfolio Optimization

Cited by 2