research
∙
09/05/2023
Breaking Barriers to Creative Expression: Co-Designing and Implementing an Accessible Text-to-Image Interface
Text-to-image generation models have grown in popularity due to their ab...
share
research
∙
07/19/2023
Beyond the ML Model: Applying Safety Engineering Frameworks to Text-to-Image Development
Identifying potential social and ethical risks in emerging machine learn...
research
∙
12/13/2022
Redefining Relationships in Music
AI tools increasingly shape how we discover, make and experience music. ...
research
∙
10/11/2022
Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
Understanding the landscape of potential harms from algorithmic systems ...
research
∙
10/06/2022
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML
Inappropriate design and deployment of machine learning (ML) systems lea...
research
∙
05/31/2022
Inducing bias is simpler than you think
Machine learning may be oblivious to human bias but it is not immune to ...
research
∙
05/27/2022
Looking at Creative ML Blindspots with a Sociological Lens
How can researchers from the creative ML/AI community and sociology of c...
research
∙
05/11/2022
Evaluation Gaps in Machine Learning Practice
Forming a reliable judgement of a machine learning (ML) model's appropri...
research
∙
04/08/2022
Disability prediction in multiple sclerosis using performance outcome measures and demographic data
Literature on machine learning for multiple sclerosis has primarily focu...
research
∙
02/26/2022
Healthsheet: Development of a Transparency Artifact for Health Datasets
Machine learning (ML) approaches have demonstrated promising results in ...
research
∙
02/25/2022
se-Shweshwe Inspired Fashion Generation
Fashion is one of the ways in which we show ourselves to the world. It i...
research
∙
12/06/2021
Ethics and Creativity in Computer Vision
This paper offers a retrospective of what we learnt from organizing the ...
research
∙
12/06/2021
Thinking Beyond Distributions in Testing Machine Learned Models
Testing practices within the machine learning (ML) community have center...
research
∙
01/16/2021
Deep Cox Mixtures for Survival Regression
Survival analysis is a challenging variation of regression modeling beca...
research
∙
07/03/2020
A Few-Shot Sequential Approach for Object Counting
In this work, we address the problem of few-shot multi-classobject count...
research
∙
02/16/2020
Reinforced active learning for image segmentation
Learning-based approaches for semantic segmentation have two inherent ch...
research
∙
10/06/2019
Neural Multisensory Scene Inference
For embodied agents to infer representations of the underlying 3D physic...
research
∙
06/14/2019
Instance Segmentation with Point Supervision
Instance segmentation methods often require costly per-pixel labels. We ...
research
∙
04/06/2019
Reinforced Imitation in Heterogeneous Action Space
Imitation learning is an effective alternative approach to learn a polic...
research
∙
03/21/2019
Towards Standardization of Data Licenses: The Montreal Data License
This paper provides a taxonomy for the licensing of data in the fields o...
research
∙
02/19/2019
Adaptive Cross-Modal Few-Shot Learning
Metric-based meta-learning techniques have successfully been applied to ...
research
∙
12/11/2018
Adversarial Framing for Image and Video Classification
Neural networks are prone to adversarial attacks. In general, such attac...
research
∙
12/04/2018
Learning Single-View 3D Reconstruction with Adversarial Training
Single-view 3D shape reconstruction is an important but challenging prob...
research
∙
07/25/2018
Where are the Blobs: Counting by Localization with Point Supervision
Object counting is an important task in computer vision due to its growi...
research
∙
06/21/2018
Fashion-Gen: The Generative Fashion Dataset and Challenge
We introduce a new dataset of 293,008 high definition (1360 x 1360 pixel...
research
∙
06/20/2018
Uncertainty in Multitask Transfer Learning
Using variational Bayes neural networks, we develop an algorithm capable...
research
∙
02/04/2018
Hierarchical Adversarially Learned Inference
We propose a novel hierarchical generative model with a simple Markovian...
research
∙
12/13/2017
Deep Prior
The recent literature on deep learning offers new tools to learn a rich ...
research
∙
05/27/2017