14 citations · 17 across the 4 of their papers we have counts for
4 papers
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models
Yunhao Ge, Jie Ren, Jiaping Zhao +4
We focus on the challenge of out-of-distribution (OOD) detection in deep learning models, a crucial aspect in ensuring reliability. Despite considerable effort, the problem remains…
Improving Zero-shot Generalization and Robustness of Multi-modal Models
Yunhao Ge, Jie Ren, Andrew Gallagher +6
Multi-modal image-text models such as CLIP and LiT have demonstrated impressive performance on image classification benchmarks and their zero-shot generalization ability is particu…
Density of States Estimation for Out-of-Distribution Detection
Warren R. Morningstar, Cusuh Ham, Andrew G. Gallagher +3
Perhaps surprisingly, recent studies have shown probabilistic model likelihoods have poor specificity for out-of-distribution (OOD) detection and often assign higher likelihoods to…
Automatic Differentiation Variational Inference with Mixtures
Warren R. Morningstar, Sharad M. Vikram, Cusuh Ham +2
Automatic Differentiation Variational Inference (ADVI) is a useful tool for efficiently learning probabilistic models in machine learning. Generally approximate posteriors learned…