Code for the Paper "A Functional Data Perspective and Baseline on Multi-Layer Out-of-Distribution Detection"

Leveraging latent representations for efficient textual OOD detection

Self-Supervised Learning for OOD Detection (NeurIPS 2019)

Tensorflow Implementation of various post hoc OOD detectors

A repo containing all the material from the Laboratory Sessions of the Deep Learning Applications course, held by Professor Andrew David Bagdanov (@bagdanov on GitHub) at the University of Florence, Italy.

Source code for the project OOD Detection of COVID-19 From Chest X-Ray Images, written as part of the KTH course DD2424, Deep Learning in Data Science:

OOD-CV dataset converter to COCO format

Python code to implement an efficient approach to unsupervised OOD detection with VAE

An end-to-end multimodal framework incorporating explicit knowledge graphs and OOD-detection. (NeurIPS23)

The implementation of DS-FL+ (Energy-based Knowledge Distillation for Communication-Efficient Federated Learning, IEICE 2024 student poster session).

Source code for 《Towards Multi-label Unknown Intent Detection》, which is accepted by COLING 2022.

Taming False Positives in Out-of-Distribution Detection with Human Feedback (AISTATS '24)

Student project regarding out-of-domain text classification methods comparison on CLINC150 dataset.

Post-hoc Out-of-Distribution Detection

Official PyTorch implementation for "SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection"

Baseline for out-of-distribution detection

STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy

[EMNLP 2023] FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score

A re-implementation project of Serra et al.: “Input complexity and out-of-distribution detection with likelihood-based generative models"