Emily Denton
Emily Denton
Verified email at google.com - Homepage
Cited by
Cited by
Deep generative image models using a laplacian pyramid of adversarial networks
E Denton, S Chintala, A Szlam, R Fergus
arXiv preprint arXiv:1506.05751, 2015
Exploiting linear structure within convolutional networks for efficient evaluation
EL Denton, W Zaremba, J Bruna, Y LeCun, R Fergus
Advances in neural information processing systems, 1269-1277, 2014
Unsupervised learning of disentangled representations from video
E Denton, V Birodkar
arXiv preprint arXiv:1705.10915, 2017
Stochastic video generation with a learned prior
E Denton, R Fergus
International Conference on Machine Learning, 1174-1183, 2018
Semi-supervised learning with context-conditional generative adversarial networks
E Denton, S Gross, R Fergus
arXiv preprint arXiv:1611.06430, 2016
Modeling others using oneself in multi-agent reinforcement learning
R Raileanu, E Denton, A Szlam, R Fergus
International conference on machine learning, 4257-4266, 2018
Towards a critical race methodology in algorithmic fairness
A Hanna, E Denton, A Smart, J Smith-Loud
Proceedings of the 2020 conference on fairness, accountability, and …, 2020
Saving face: Investigating the ethical concerns of facial recognition auditing
ID Raji, T Gebru, M Mitchell, J Buolamwini, J Lee, E Denton
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 145-151, 2020
User conditional hashtag prediction for images
E Denton, J Weston, M Paluri, L Bourdev, R Fergus
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
ChromoHub: a data hub for navigators of chromatin-mediated signalling
L Liu, XT Zhen, E Denton, BD Marsden, M Schapira
Bioinformatics 28 (16), 2205-2206, 2012
How to train a GAN? Tips and tricks to make GANs work
S Chintala, E Denton, M Arjovsky, M Mathieu
Github. com, 2016
A global assessment of cancer genomic alterations in epigenetic mechanisms
MA Shah, EL Denton, CH Arrowsmith, M Lupien, M Schapira
Epigenetics & chromatin 7 (1), 1-15, 2014
Data and its (dis) contents: A survey of dataset development and use in machine learning research
A Paullada, ID Raji, EM Bender, E Denton, A Hanna
Patterns 2 (11), 100336, 2021
Social biases in NLP models as barriers for persons with disabilities
B Hutchinson, V Prabhakaran, E Denton, K Webster, Y Zhong, S Denuyl
arXiv preprint arXiv:2005.00813, 2020
Characterising bias in compressed models
S Hooker, N Moorosi, G Clark, S Bengio, E Denton
arXiv preprint arXiv:2010.03058, 2020
Towards accountability for machine learning datasets: Practices from software engineering and infrastructure
B Hutchinson, A Smart, A Hanna, E Denton, C Greer, O Kjartansson, ...
Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021
Detecting bias with generative counterfactual face attribute augmentation
E Denton, B Hutchinson, M Mitchell, T Gebru
arXiv e-prints, arXiv: 1906.06439, 2019
Diversity and inclusion metrics in subset selection
M Mitchell, D Baker, N Moorosi, E Denton, B Hutchinson, A Hanna, ...
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 117-123, 2020
Bringing the people back in: Contesting benchmark machine learning datasets
E Denton, A Hanna, R Amironesei, A Smart, H Nicole, MK Scheuerman
arXiv preprint arXiv:2007.07399, 2020
Learning goal embeddings via self-play for hierarchical reinforcement learning
S Sukhbaatar, E Denton, A Szlam, R Fergus
arXiv preprint arXiv:1811.09083, 2018
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