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05/24/2023
Deep Learning for Survival Analysis: A Review
The influx of deep learning (DL) techniques into the field of survival a...
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12/01/2022
Re-evaluating sample efficiency in de novo molecule generation
De novo molecule generation can suffer from data inefficiency; requiring...
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10/17/2022
Conditional Neural Processes for Molecules
Neural processes (NPs) are models for transfer learning with properties ...
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05/25/2022
Factorized Structured Regression for Large-Scale Varying Coefficient Models
Recommender Systems (RS) pervade many aspects of our everyday digital li...
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02/12/2022
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis
Survival analysis (SA) is an active field of research that is concerned ...
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12/09/2021
Evaluation of survival distribution predictions with discrimination measures
In this paper we consider how to evaluate survival distribution predicti...
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10/29/2021
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design
The field of machine learning for drug discovery is witnessing an explos...
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04/28/2021
Mundus vult decipi, ergo decipiatur: Visual Communication of Uncertainty in Election Polls
Election poll reporting often focuses on mean values and only subordinat...
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02/19/2021
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
Drug discovery and development is an extremely complex process, with hig...
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11/11/2020
Semi-Structured Deep Piecewise Exponential Models
We propose a versatile framework for survival analysis that combines adv...
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08/18/2020
mlr3proba: An R Package for Machine Learning in Survival Analysis
As machine learning has become increasingly popular over the last few de...
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06/27/2020
A General Machine Learning Framework for Survival Analysis
The modeling of time-to-event data, also known as survival analysis, req...
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08/09/2019
Concepts and Applications of Conformal Prediction in Computational Drug Discovery
Estimating the reliability of individual predictions is key to increase ...
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04/12/2019
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout
While the use of deep learning in drug discovery is gaining increasing a...
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11/22/2018
KekuleScope: improved prediction of cancer cell line sensitivity using convolutional neural networks trained on compound images
The application of convolutional neural networks (ConvNets) to harness h...
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09/24/2018
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks
Deep learning architectures have proved versatile in a number of drug di...
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07/15/2018
KOALA: A new paradigm for election coverage
Common election poll reporting is often misleading as sample uncertainty...
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06/04/2018
pammtools: Piece-wise exponential Additive Mixed Modeling tools
This article introduces the pammtools package, which facilitates data tr...
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11/23/2014
