EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks
Abstract In recent years, Deep Learning models have shown a great performance in
complex optimization problems. They generally require large training datasets, which is a …
complex optimization problems. They generally require large training datasets, which is a …
Predicting the Encoding Error of SIRENs
J Vonderfecht, F Liu - arXiv preprint arXiv:2410.21645, 2024 - arxiv.org
Implicit Neural Representations (INRs), which encode signals such as images, videos, and
3D shapes in the weights of neural networks, are becoming increasingly popular. Among …
3D shapes in the weights of neural networks, are becoming increasingly popular. Among …
Neural Architecture Search for Explainable Networks
One of the main challenges in machine learning is providing understandable explanations
for complex models. Despite outperforming humans in many tasks, machine learning …
for complex models. Despite outperforming humans in many tasks, machine learning …
Cost-aware graph generation: A deep bayesian optimization approach
Graph-structured data is ubiquitous throughout the natural and social sciences, ranging from
complex drug molecules to artificial neural networks. Evaluating their functional properties …
complex drug molecules to artificial neural networks. Evaluating their functional properties …
EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks
In recent years, Deep Learning models have shown a great performance in complex
optimization problems. They generally require large training datasets, which is a limitation in …
optimization problems. They generally require large training datasets, which is a limitation in …