research
∙
09/23/2022
Facilitating Change Implementation for Continuous ML-Safety Assurance
We propose a method for deploying a safety-critical machine-learning com...
share
research
∙
08/03/2021
Categorical EHR Imputation with Generative Adversarial Nets
Electronic Health Records often suffer from missing data, which poses a ...
research
∙
07/26/2021
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models
Recurrent neural network based solutions are increasingly being used in ...
research
∙
06/08/2021
Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
Recommender systems are often designed based on a collaborative filterin...
research
∙
06/01/2021
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
Deep neural networks are increasingly being used for the analysis of med...
research
∙
07/02/2020
Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score
Randomized controlled trials typically analyze the effectiveness of trea...
research
∙
12/05/2018
Understanding Individual Decisions of CNNs via Contrastive Backpropagation
A number of backpropagation-based approaches such as DeConvNets, vanilla...
research
∙
07/06/2017
Tensor-Train Recurrent Neural Networks for Video Classification
The Recurrent Neural Networks and their variants have shown promising pe...
research
∙
02/08/2016
Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks
In clinical data sets we often find static information (e.g. patient gen...
research
∙
11/25/2015
