Emily Denton | DeepAI

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∙ 05/19/2023

AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia

This paper presents a community-centered study of cultural limitations o...

0 Rida Qadri, et al. ∙

∙ 11/22/2022

City-Wide Perceptions of Neighbourhood Quality using Street View Images

The interactions of individuals with city neighbourhoods is determined, ...

0 Emily Muller, et al. ∙

∙ 06/09/2022

CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation

Human annotated data plays a crucial role in machine learning (ML) resea...

0 Mark Díaz, et al. ∙

∙ 05/23/2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

We present Imagen, a text-to-image diffusion model with an unprecedented...

0 Chitwan Saharia, et al. ∙

∙ 12/08/2021

Whose Ground Truth? Accounting for Individual and Collective Identities Underlying Dataset Annotation

Human annotations play a crucial role in machine learning (ML) research ...

12 Emily Denton, et al. ∙

∙ 12/06/2021

Ethics and Creativity in Computer Vision

This paper offers a retrospective of what we learnt from organizing the ...

0 Negar Rostamzadeh, et al. ∙

∙ 12/03/2021

Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research

Benchmark datasets play a central role in the organization of machine le...

0 Bernard Koch, et al. ∙

∙ 11/26/2021

AI and the Everything in the Whole Wide World Benchmark

There is a tendency across different subfields in AI to valorize a small...

0 Inioluwa Deborah Raji, et al. ∙

∙ 08/09/2021

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

Data is a crucial component of machine learning. The field is reliant on...

0 Morgan Klaus Scheuerman, et al. ∙

∙ 12/09/2020

Data and its (dis)contents: A survey of dataset development and use in machine learning research

Datasets have played a foundational role in the advancement of machine l...

0 Amandalynne Paullada, et al. ∙

∙ 10/23/2020

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure

Rising concern for the societal implications of artificial intelligence ...

0 Ben Hutchinson, et al. ∙

∙ 10/06/2020

Characterising Bias in Compressed Models

The popularity and widespread use of pruning and quantization is driven ...

0 Sara Hooker, et al. ∙

∙ 07/14/2020

Bringing the People Back In: Contesting Benchmark Machine Learning Datasets

In response to algorithmic unfairness embedded in sociotechnical systems...

0 Emily Denton, et al. ∙

∙ 05/02/2020

Social Biases in NLP Models as Barriers for Persons with Disabilities

Building equitable and inclusive NLP technologies demands consideration ...

0 Ben Hutchinson, et al. ∙

∙ 02/09/2020

Diversity and Inclusion Metrics in Subset Selection

The ethical concept of fairness has recently been applied in machine lea...

23 Margaret Mitchell, et al. ∙

∙ 01/03/2020

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

Although essential to revealing biased performance, well intentioned att...

0 Inioluwa Deborah Raji, et al. ∙

∙ 12/08/2019

Towards a Critical Race Methodology in Algorithmic Fairness

We examine the way race and racial categories are adopted in algorithmic...

0 Alex Hanna, et al. ∙

∙ 06/14/2019

Detecting Bias with Generative Counterfactual Face Attribute Augmentation

We introduce a simple framework for identifying biases of a smiling attr...

0 Emily Denton, et al. ∙

∙ 11/22/2018

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning

In hierarchical reinforcement learning a major challenge is determining ...

0 Sainbayar Sukhbaatar, et al. ∙

∙ 02/26/2018

Modeling Others using Oneself in Multi-Agent Reinforcement Learning

We consider the multi-agent reinforcement learning setting with imperfec...

0 Roberta Raileanu, et al. ∙

∙ 02/21/2018

Stochastic Video Generation with a Learned Prior

Generating video frames that accurately predict future world states is c...

0 Emily Denton, et al. ∙

∙ 05/31/2017

Unsupervised Learning of Disentangled Representations from Video

We present a new model DrNET that learns disentangled image representati...

0 Emily Denton, et al. ∙

∙ 11/19/2016

Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

We introduce a simple semi-supervised learning approach for images based...

0 Emily Denton, et al. ∙

∙ 06/18/2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

In this paper we introduce a generative parametric model capable of prod...

0 Emily Denton, et al. ∙

∙ 04/02/2014

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

We present techniques for speeding up the test-time evaluation of large ...

0 Emily Denton, et al. ∙

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