Learning curves for decision making in supervised machine learning: A survey
F Mohr, JN van Rijn - Machine Learning, 2024 - Springer
Learning curves are a concept from social sciences that has been adopted in the context of
machine learning to assess the performance of a learning algorithm with respect to a certain …
machine learning to assess the performance of a learning algorithm with respect to a certain …
Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN
We present our work on developing and training scalable graph foundation models (GFM)
using HydraGNN, a multi-headed graph convolutional neural network architecture …
using HydraGNN, a multi-headed graph convolutional neural network architecture …
[HTML][HTML] Combining survey and census data for improved poverty prediction using semi-supervised deep learning
This paper presents a methodology for predicting poverty using semi-supervised learning
techniques, specifically pseudo-labeling, and deep learning algorithms. Standard poverty …
techniques, specifically pseudo-labeling, and deep learning algorithms. Standard poverty …
Selecting pre-trained models for transfer learning with data-centric meta-features
M van den Nieuwenhuijzen, C Doerr… - AutoML …, 2024 - hal.sorbonne-universite.fr
When applying a neural network to address a new learning problem, rather than training a
network from scratch, it is common practice to utilise a network pre-trained on a related …
network from scratch, it is common practice to utilise a network pre-trained on a related …