Unsupervised Error Detection through Clustering. Work performed at IISc Bangalore
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Updated
Jul 31, 2020 - Jupyter Notebook
Unsupervised Error Detection through Clustering. Work performed at IISc Bangalore
Attribute-Inference for out-of-set Detection
👾 Outlier Exposure with Generative Models
Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR2021).
[ECCV'22 Oral] Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. Dealing with out-of-distribution detection or open-set recognition in semantic segmentation.
Epistemic uncertainty, sometimes referred to as model uncertainty, describes what the model does not know because training data was not appropriate. Modelling epistemic uncertainty is crucial to prevent ill advised discussion making due to over confident models.
Hugging Face Space for showcasing how out-of-distribution (OOD) detection works.
Implementation of "Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences" (ICDM2023)
Out-of-Distribution Detection For Forgery Images Using Digital Watermarking
Official repository for the paper entitled "Feature-based Out-of-Distribution Detection for Medical Imaging Segmentation".
The accompanying code to the publication "Out-of-Distribution Detection using Outlier Detection Methods"
Python experiments for https://arxiv.org/abs/1904.12286.
Official PyTorch Implementation of Meta-Query-Net NeurIPS 2022.
Fooling Machine Learning Models: A Novel Out-of-Distribution Attack through Generative Adversarial Networks
Benchmarking Bayesian Deep Learning for Out-of-Distribution Detection
CSCI2470 Deep Learning Spring 2024: Enhancing Out-of-Distribution Object Detection with CLIP: A Vision-Language Approach
Uncertainty quantification and out-of-distribution detection using surjective normalizing flows
Evaluation of Perturbation Methods for Deep Learning Explanation Methods
[IV 2024] Official code for "Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection"
Out-of-Distribution Detection for Text Classification Using Stochastic Attention and the Deep Deterministic Uncertainty Framework
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