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08/30/2023
Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge
A growing body of research has explored how to support humans in making ...
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12/11/2022
Towards a Learner-Centered Explainable AI: Lessons from the learning sciences
In this short paper, we argue for a refocusing of XAI around human learn...
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10/05/2020
Probabilistic 3D surface reconstruction from sparse MRI information
Surface reconstruction from magnetic resonance (MR) imaging data is indi...
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07/19/2020
One-Shot Learning for Language Modelling
Humans can infer a great deal about the meaning of a word, using the syn...
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06/18/2020
Detecting Affective Flow States of Knowledge Workers Using Physiological Sensors
Flow-like experiences at work are important for productivity and worker ...
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06/17/2020
Pain Intensity Estimation from Mobile Video Using 2D and 3D Facial Keypoints
Managing post-surgical pain is critical for successful surgical outcomes...
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04/27/2020
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization
Despite recent advances in natural language processing and other languag...
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02/26/2020
Universal Phone Recognition with a Multilingual Allophone System
Multilingual models can improve language processing, particularly for lo...
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06/05/2018
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease
Graphs are widely used as a natural framework that captures interactions...
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04/11/2018
Attention U-Net: Learning Where to Look for the Pancreas
We propose a novel attention gate (AG) model for medical imaging that au...
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11/04/2017
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
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03/08/2017
Spectral Graph Convolutions for Population-based Disease Prediction
Exploiting the wealth of imaging and non-imaging information for disease...
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03/07/2017