datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dml-fl-iot-ids-dynamic3L-K3PU-Net-Outputsdml-fl-iot-ids-dynamic3L-K5dml-fl-iot-ids-dynamic3L-K10dml-fl-iot-ids-static3Lwawadmlab_roomba_evalwawa_manifold_pluswawa_manifolddml-fl-iot-ids-baseline-rerunV1wds_vtab-dmlabdm_lab
UNDER CONSTRUCTION !!!
DeepMind-Lab 30 Benchmark
This dataset contains expert trajectories generated by a Dreamer V3 reinforcement learning agent trained on each of the 30 environments in DMLab-30. Contrary to other datasets, we provide image observations instead of states.
Dataset Usage
Regular usage (for the domain acrobot with task swingup):
from datasets import load_dataset
train_dataset = load_dataset("EpicPinkPenguin/visual_dm_control"… See the full description on the dataset page: https://huggingface.co/datasets/ramu0e/dm_lab.dmlab_figure8_evaldmlabdm_lab
UNDER CONSTRUCTION !!!
DeepMind-Lab 30 Benchmark
This dataset contains expert trajectories generated by a Dreamer V3 reinforcement learning agent trained on each of the 30 environments in DMLab-30. Contrary to other datasets, we provide image observations instead of states.
Dataset Usage
Regular usage (for the domain acrobot with task swingup):
from datasets import load_dataset
train_dataset = load_dataset("EpicPinkPenguin/visual_dm_control"… See the full description on the dataset page: https://huggingface.co/datasets/EpicPinkPenguin/dm_lab.dml-fl-iot-ids-diagnosticDMLabwds_vtab-dmlab_test
DMLab Frames (Test set only)
Original paper: The Visual Task Adaptation Benchmark
Homepage: https://github.com/google-research/task_adaptation
Bibtex:
@article{zhai2019visual,
title={The Visual Task Adaptation Benchmark},
author={Xiaohua Zhai and Joan Puigcerver and Alexander Kolesnikov and
Pierre Ruyssen and Carlos Riquelme and Mario Lucic and
Josip Djolonga and Andre Susano Pinto and Maxim Neumann and
Alexey Dosovitskiy… See the full description on the dataset page: https://huggingface.co/datasets/djghosh/wds_vtab-dmlab_test.dml-fl-iot-ids
DML-FL IoT IDS Benchmark Results
Results from the paper: Dynamic Multilevel Clustered Federated Learning for IoT Intrusion Detection
Grid (72 total runs)
Dimension
Options
Models
CNN, BiLSTM, CNN+BiLSTM, Transformer (fixed)
FL Algorithms
FedAvg, FedProx, FedNova
Datasets
CICIDS2017, UNSW-NB15, Edge-IIoTset
Distributions
IID, Non-IID (Dirichlet α=0.5)
Clients / Rounds
30 clients / 30 rounds / 3 local epochs
Files
File… See the full description on the dataset page: https://huggingface.co/datasets/JabaleNurAdnan/dml-fl-iot-ids.p2-dml-etf-payoffs-resultswds_dmlabDML-Financesgithub-issues
Dataset Card for "github-issues"
More Information needed
DMLab_Latentdml_task_1dml-fl-iot-ids-baselineGene-DML_st_datasets
Processed Data for Training/Testing Gene-DML Framework
Gene-DML: Dual-Pathway Multi-Level Discrimination for Gene Expression Prediction from Histopathology Images (accepted by WACV2026). Please kindly refer to our paper and code.
Structure
st_data/
├── her2st/ # HER2ST dataset
│ ├── ST-cnts/ # Gene expression count files
│ ├── ST-imgs/ # Histopathology images
│ ├── ST-spotfiles/ #… See the full description on the dataset page: https://huggingface.co/datasets/YXSong000/Gene-DML_st_datasets.phi-model-datadMLINJBtDMLLM_debug_dataset