10 citations · 15 across the 5 of their papers we have counts for
5 papers
Logit Scaling for Out-of-Distribution Detection
Andrija Djurisic, Rosanne Liu, Mladen Nikolic
The safe deployment of machine learning and AI models in open-world settings hinges critically on the ability to detect out-of-distribution (OOD) data accurately, data samples that…
Engineering an Efficient Object Tracker for Non-Linear Motion
Momir Adžemović, Predrag Tadić, Andrija Petrović +1
The goal of multi-object tracking is to detect and track all objects in a scene while maintaining unique identifiers for each, by associating their bounding boxes across video fram…
Beyond Kalman Filters: Deep Learning-Based Filters for Improved Object Tracking
Momir Adžemović, Predrag Tadić, Andrija Petrović +1
Traditional tracking-by-detection systems typically employ Kalman filters (KF) for state estimation. However, the KF requires domain-specific design choices and it is ill-suited to…
Incorporating LLM Priors into Tabular Learners
Max Zhu, Siniša Stanivuk, Andrija Petrovic +2
We present a method to integrate Large Language Models (LLMs) and traditional tabular data classification techniques, addressing LLMs challenges like data serialization sensitivity…
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces
Max Zhu, Katarzyna Kobalczyk, Andrija Petrovic +4
Despite the prevalence of tabular datasets, few-shot learning remains under-explored within this domain. Existing few-shot methods are not directly applicable to tabular datasets d…