Unsupervised Error Detection through Clustering. Work performed at IISc Bangalore

Attribute-Inference for out-of-set Detection

🤔 Out-of-Distribution Detection with Logical Reasoning

Official PyTorch Implementation of Meta-Query-Net NeurIPS 2022.

NECO paper presented @ICLR2024

Out-of-distribution detection using Variational Auto-Encoder

Probabilistic Trust Intervals For Detecting Out of Distribution Images

👾 Outlier Exposure with Generative Models

Official PyTorch code for UAI 2023 paper "Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow"

[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.

Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR2021).

Deep Learning (CS F425): Course Project

Uncertainty quantification and out-of-distribution detection using surjective normalizing flows

Official PyTorch code for "Transformer-based out-of-distribution detection for clinically safe segmentation"

Implementation of "Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences" (ICDM2023)

Code and data for the paper "In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation"

PyTorch implementation of DeepMSVDD

Evaluation of Perturbation Methods for Deep Learning Explanation Methods