11 to 13 of 13 Results
Oct 15, 2021
Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1
Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab |
Oct 5, 2021 - PN 6-6
Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1
We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details. |
Mar 23, 2021 - PN 6-3
Holzmüller, David, 2021, "Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression", https://doi.org/10.18419/darus-1771, DaRUS, V1
This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally pro... |