1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
An Efficient Model-Agnostic Approach for Uncertainty Estimation in Data-Restricted Pedometric Applications
Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers +1
This paper introduces a model-agnostic approach designed to enhance uncertainty estimation in the predictive modeling of soil properties, a crucial factor for advancing pedometrics…
cs.LG2024
An Empirical Study on Improving SimCLR's Nonlinear Projection Head using Pretrained Autoencoder Embeddings
Andreas Schliebitz, Heiko Tapken, Martin Atzmueller
This paper focuses on improving the effectiveness of the standard 2-layer MLP projection head featured in the SimCLR framework through the use of pretrained autoencoder embeddings.…