407 citations · 495 across the 17 of their papers we have counts for
5 papers · 1 filter
Adaptive Hierarchical Graph Cut for Multi-granularity Out-of-distribution Detection
Xiang Fang, Arvind Easwaran, Blaise Genest +1
This paper focuses on a significant yet challenging task: out-of-distribution detection (OOD detection), which aims to distinguish and reject test samples with semantic shifts, so…
Your Data Is Not Perfect: Towards Cross-Domain Out-of-Distribution Detection in Class-Imbalanced Data
Xiang Fang, Arvind Easwaran, Blaise Genest +1
Previous OOD detection systems only focus on the semantic gap between ID and OOD samples. Besides the semantic gap, we are faced with two additional gaps: the domain gap between so…
Unified Discrete Diffusion for Simultaneous Vision-Language Generation
Minghui Hu, Chuanxia Zheng, Heliang Zheng +5
The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In thi…
Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification
Rakesh Katuwal, P. N. Suganthan
Extreme learning machine (ELM), which can be viewed as a variant of Random Vector Functional Link (RVFL) network without the input-output direct connections, has been extensively u…
Random Vector Functional Link Neural Network based Ensemble Deep Learning
Rakesh Katuwal, P. N. Suganthan, M. Tanveer
In this paper, we propose a deep learning framework based on randomized neural network. In particular, inspired by the principles of Random Vector Functional Link (RVFL) network, w…