LG AI Research· EXAONE

[NeurIPS 2023] Out-of-Distribution Detection via Synthetic Outlier Generation Part 1

Data Intelligence (DI) Lab at LG AI Research presented their study titled “Diffusion-Based Semantic-Discrepant Outlier Generation for Out-of-Distribution Detection” [1] at the NeurIPS 2023 SyntheticData4ML Workshop. Together with researchers, the DI Lab also discussed various synthetic outlier generation methods and suitable detection approaches to improve out-of-distribution detection performance. To share some of the important insights gained along the way, we will explore the research paper LG AI Research has published, as well as some of the other meaningful ones that would be worthwhile to examine. ▶ Out-of-Distribution Detection via Synthetic Outlier Generation ㆍ Part 1 DI Lab Suhee Yoon ㆍ Part 2 DI Lab Sanghyu Yoon ( Link ) Out-of-Distribution Detection Out-of-Distribution (OOD) Detection is the problem of detecting whether a new given data point belongs to an existing In-Distribution (ID) or not. For many years, OOD Detection has been used in a variety of real world applications, including medical diagnostics, autonomous driving, prediction, and more. …

Announced

13 Feb 2024 00:00 UTC

Detected

28 Aug 2026 22:20 UTC (+927d after)