my MA thesis (code, paper & presentation) about adversarial out-of-distribution detection
A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.
[EMNLP 2023] FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score
A list of accepted papers in AAAI 2021 about anomaly detection.
Official PyTorch implementation of "Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data" (NeurIPS'23)
An end-to-end vision-language framework incorporating explicit knowledge graphs and OOD-detection. (NeurIPS 23)
[ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"
[Under Progress] Code & Data for the AAAI 2020 Paper "Likelihood Ratios and Generative Classifiers For Unsupervised OOD Detection In Task-Based Dialog" - Varun Gangal, Abhinav Arora, Arash Einolghozati, Sonal Gupta
The implementation of DS-FL+ (Energy-based Knowledge Distillation for Communication-Efficient Federated Learning, IEICE 2024 student poster session).
PyTorch Implementation of ECCV 2024 OOD-CV Workshop SSB Challenge (Open-Set Recognition Track) - 1st Place
Source code for 《Energy-based Unknown Intent Detection with Data Manipulation》, which is accepted by Findings of ACL, 2021.
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.
"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?" (CVPR 2024)
[ECCV'22 Oral] Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
Student project regarding out-of-domain text classification methods comparison on CLINC150 dataset.
Self-Supervised Learning for OOD Detection (NeurIPS 2019)
Tensorflow Implementation of various post hoc OOD detectors
[ICML 2024] "Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection"
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