outlier
Datasets
All datasets matching “outlier”QCed_1000Genomes
Dataset Card for 1000 Genomes Project
This dataset provides processed genetic data from the 1000 Genomes Project, specifically prepared for Mendelian randomization (MR) analyses, making it easier for researchers to conduct MR analyses without extensive data preparation.
Dataset Sources
Original Data Source: 1000 Genomes Project (https://www.internationalgenome.org/)
Dataset Structure
The dataset is organized by chromosomes and populations.
jinyang-omentum-rmats-outlier-fixed-biology-results-v1
jinyang-omentum-rmats-outlier-fixed-biology-results-v1
Biology of the k=2 subgroups from jinyang-omentum-rmats-outlier-fixed-clustering (cluster1 n=116 / cluster2 n=50, 166 outlier-excluded omentum samples; expression analyses on the 160-sample TPM-labeled intersection). CAVEAT (stated plainly, not buried): cluster1/cluster2 are collinear with sequencing platform to within one sample -- cluster 2 contains ZERO NovaSeq-6000 samples and cluster 1 is 113/116 NovaSeq-6000. The… See the full description on the dataset page: https://huggingface.co/datasets/depinwang/jinyang-omentum-rmats-outlier-fixed-biology-results-v1.jinyang-omentum-rmats-outlier-fixed-clustering-results-v1
jinyang-omentum-rmats-outlier-fixed-clustering-results-v1
Patient-level permutation-null control, N=50 (canary; final extends to N=200). IMPORTANT CAVEAT (see 01_pipeline.R header and EXPERIMENT_README.md): this tests circularity in the CLUSTERING+LOG-RANK steps ONLY -- the 651 candidate events are FIXED across every permutation draw (they were externally selected using the TRUE survival outcome, not re-derived by this pipeline), so this control does NOT correct for… See the full description on the dataset page: https://huggingface.co/datasets/depinwang/jinyang-omentum-rmats-outlier-fixed-clustering-results-v1.bimanual-so101-position-cup-for-coffee-3-no-outlierThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "bi_so_follower",
"total_episodes": 300,
"total_frames": 87235,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 15,
"splits": {
"train": "0:300"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/apaszynska/bimanual-so101-position-cup-for-coffee-3-no-outlier.cifar10-outlier
Dataset Card for "cifar10-outlier"
📚 This dataset is an enriched version of the CIFAR-10 Dataset.
The workflow is described in the medium article: Changes of Embeddings during Fine-Tuning of Transformers.
Explore the Dataset
The open source data curation tool Renumics Spotlight allows you to explorer this dataset. You can find a Hugging Face Spaces running Spotlight with this dataset here:
Full Version (High hardware requirement)… See the full description on the dataset page: https://huggingface.co/datasets/renumics/cifar10-outlier.repro-mamba-icl-outliers-actual
Actual Mamba ICL Outlier Reproduction Artifacts
Measured reproduction artifacts for ICML 2026 paper C41aLahRXZ, "How Can Mamba Learn In Context with Outliers and Generalize Provably?".
The scripts implement the paper synthetic setup: Eq. (3), Definitions 1-2, hinge-loss SGD, one-layer Mamba and linear Transformer control. Outputs in actual_outputs/ are from 5 seeds, 4000 SGD iterations, batch 128, and 4000 prompts per evaluation point.
HF GPU evidence:… See the full description on the dataset page: https://huggingface.co/datasets/Srishti280992/repro-mamba-icl-outliers-actual.