representation-learning
deep-multimodal-representation-learning-for-stellar-spectraDataset used in the paper "Deep Multimodal Representation Learning for Stellar Spectra".
Dataset of Milky Way stars based on selection from https://ui.adsabs.harvard.edu/abs/2024A&A...682A...9G,
which is based on ESA/Gaia/DPAC and APOGEE surveys.
This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia),
processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).
Funding… See the full description on the dataset page: https://huggingface.co/datasets/christianschwarz/deep-multimodal-representation-learning-for-stellar-spectra.RepresentationLearning-dataset
RepresentationLearning dataset
Preprocessed WiFi packets for three wireless tasks, used to train and attack the
multi-task representations in
RepresentationLearning.
Pretrained models and the run registry are in
Aadharsh/RepresentationLearning-models.
The packets are derived from the ORACLE RF fingerprinting dataset
(16 USRP X310 transmitters recorded at 11 distances, 2–62 ft).
Files
File
Size
Contents
OracleDatasetProcessed-arranged.tar.gz
3.3 GB
416… See the full description on the dataset page: https://huggingface.co/datasets/Aadharsh/RepresentationLearning-dataset.Latent-LMDB-Content-Style-Disentangled-Representation-Learning
code-representation-learningMask2Rep-Self-Supervised-Image-Representation-Learningrepro-cross-tactile-sensor-representation-learningrepro-sgera-stein-guided-ecg-report-alignment-for-ecg-representation-learningrepro-sgera-stein-guided-ecg-report-alignment-for-ecg-representation-learningrepro-the-geometric-mechanics-of-contrastive-representation-learning-alignment-potentials-entrop