Codalab competitions: An open source platform to organize scientific challenges
CodaLab Competitions is an open source web platform designed to help data scientists and
research teams to crowd-source the resolution of machine learning problems through the …
research teams to crowd-source the resolution of machine learning problems through the …
The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke
SL Liew, A Zavaliangos‐Petropulu… - Human brain …, 2022 - Wiley Online Library
The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke
Recovery working group is to understand brain and behavior relationships using well …
Recovery working group is to understand brain and behavior relationships using well …
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
We contribute to micro-data model-based reinforcement learning (MBRL) by rigorously
comparing popular generative models using a fixed (random shooting) control agent. We …
comparing popular generative models using a fixed (random shooting) control agent. We …
Evolution of the historian data entry application: Supporting transcribathons in the digital humanities through mdd
Death and Burial Data: Ireland 1864–1922 (DBDIrl), is a digital humanities project, which
uses historical civil registration of death as its primary dataset. The overarching aim of this …
uses historical civil registration of death as its primary dataset. The overarching aim of this …
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning
In model-based reinforcement learning, most algorithms rely on simulating trajectories from
one-step models of the dynamics learned on data. A critical challenge of this approach is the …
one-step models of the dynamics learned on data. A critical challenge of this approach is the …
Sharing and performance optimization of reproducible workflows in the cloud
Scientific workflows play a vital role in modern science as they enable scientists to specify,
share and reuse computational experiments. To maximizethe benefits, workflows need to …
share and reuse computational experiments. To maximizethe benefits, workflows need to …
The 2018 climate informatics hackathon: Hurricane intensity forecast
The 2018 Climate Informatics hackathon focused on forecasting the hurricane intensities,
and there was 35 participants. Specifically, the goal was to predict the intensity of tropical …
and there was 35 participants. Specifically, the goal was to predict the intensity of tropical …
AI Competitions and Benchmarks: How to ensure a long-lasting impact of a challenge with post-challenge paper, benchmarks and other dissemination action
Organising an AI challenge does not end with the final event. The long-lasting impact also
needs to be organised. This chapter covers the various activities after the challenge is …
needs to be organised. This chapter covers the various activities after the challenge is …
Reproducing scientific experiment with cloud devops
The reproducibility of scientific experiment is vital for the advancement of disciplines based
on previous work. To achieve this goal, many researchers focus on complex methodology …
on previous work. To achieve this goal, many researchers focus on complex methodology …
Recent Advances in Tropical Cyclone Forecasting Using Machine Learning on Reanalysis and Remote Sensing
S GIFFARD‐ROISIN - Multitemporal Earth Observation Image …, 2024 - books.google.com
In this chapter, we will show how the recent advances of machine learning (ML) and in
particular deep learning (DL) can be applied to one major natural hazard forecasting …
particular deep learning (DL) can be applied to one major natural hazard forecasting …