The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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Updated
Jun 7, 2024 - Python
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Benchmarking Generalized Out-of-Distribution Detection
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
Implementation of "Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences" (ICDM2023)
Code and Data Repo for Paper "Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning"
[ICLR 2024] R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
Fooling Machine Learning Models: A Novel Out-of-Distribution Attack through Generative Adversarial Networks
CSCI2470 Deep Learning Spring 2024: Enhancing Out-of-Distribution Object Detection with CLIP: A Vision-Language Approach
Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.
[ICCV'23 Oral] Unmasking Anomalies in Road-Scene Segmentation
A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization
NECO paper presented @ICLR2024
[IV 2024] Official code for "Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection"
The official implementation of CVPR 24' Paper "Learning Transferable Negative Prompts for Out-of-Distribution Detection"
NeurIPS22 "RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection"
Heatmap-based Out-of-Distribution Detection (WACV 2023)
Out-of-Distribution Detection for Monocular Depth Estimation (ICCV 2023)
PyTorch implementation of MCM (Delving into out-of-distribution detection with vision-language representations), NeurIPS 2022
🤔 Out-of-Distribution Detection with Logical Reasoning
Package to accelerate research on generalized out-of-distribution (OOD) detection.
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