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Found 6 papers, 1 papers with code
Finding Dino: A plug-and-play framework for unsupervised detection of out-of-distribution objects using prototypes
It is an inference-based method that does not require training on the domain dataset and relies on extracting relevant features from self-supervised pre-trained models.
Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes
In this work, we propose a novel interpretable-by-design method, ProtoVerse, to find relevant sub-parts of vertebral fractures (prototypes) that reliably explain the model's decision in a human-understandable way.
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection
As the use of machine learning continues to expand, the importance of ensuring its safety cannot be overstated.
Efficient Bi-Directional Verification of ReLU Networks via Quadratic Programming
Solving the single initial QP already results in a lower bound on the DtDB and can be used as a robustness certificate of the classifier around a given sample.
GhostLink: Latent Network Inference for Influence-aware Recommendation
As additional use-cases, we show that GhostLink can be used to differentiate between users' latent preferences and influenced ones, as well as to detect influential users based on the learned influence graph.
Item Recommendation with Continuous Experience Evolution of Users using Brownian Motion
Online review communities are dynamic as users join and leave, adopt new vocabulary, and adapt to evolving trends.
