Daniel Coelho de Castro | DeepAI

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∙ 07/31/2023

No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging

As machine learning methods gain prominence within clinical decision-mak...

0 Charles Jones, et al. ∙

∙ 01/11/2023

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Self-supervised learning in vision-language processing exploits semantic...

11 Shruthi Bannur, et al. ∙

∙ 08/23/2022

Deep Structural Causal Shape Models

Causal reasoning provides a language to ask important interventional and...

22 Rajat Rasal, et al. ∙

∙ 04/21/2022

Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing

Multi-modal data abounds in biomedicine, such as radiology images and re...

2 Benedikt Boecking, et al. ∙

∙ 06/11/2020

Deep Structural Causal Models for Tractable Counterfactual Inference

We formulate a general framework for building structural causal models (...

48 Nick Pawlowski, et al. ∙

∙ 12/17/2019

Causality matters in medical imaging

This article discusses how the language of causality can shed new light ...

24 Daniel Coelho de Castro, et al. ∙

∙ 10/29/2019

Domain Generalization via Model-Agnostic Learning of Semantic Features

Generalization capability to unseen domains is crucial for machine learn...

21 Qi Dou, et al. ∙

∙ 10/10/2019

Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects

This is an empirical study to investigate the impact of scanner effects ...

22 Ben Glocker, et al. ∙

∙ 03/06/2019

Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing

We investigate discrete spin transformations, a geometric framework to m...

0 Loic Le Folgoc, et al. ∙

∙ 11/19/2018

Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model

Current face recognition systems typically operate via classification in...

14 Daniel Coelho de Castro, et al. ∙

∙ 09/27/2018

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning

Revealing latent structure in data is an active field of research, havin...

22 Daniel Coelho de Castro, et al. ∙

∙ 07/20/2018

From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data

Current face recognition systems robustly recognize identities across a ...

8 Daniel Coelho de Castro, et al. ∙

∙ 06/07/2018

Semi-Supervised Learning via Compact Latent Space Clustering

We present a novel cost function for semi-supervised learning of neural ...

2 Konstantinos Kamnitsas, et al. ∙

∙ 06/07/2018

Nonparametric Density Flows for MRI Intensity Normalisation

With the adoption of powerful machine learning methods in medical image ...

0 Daniel Coelho de Castro, et al. ∙

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