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20162024
most citedA Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

2.7k citations · 4.6k across the 40 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.LG2023★ 3 cited

A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges

Maryam Zare, Parham M. Kebria, Abbas Khosravi +1

In recent years, the development of robotics and artificial intelligence (AI) systems has been nothing short of remarkable. As these systems continue to evolve, they are being util…

cs.LG2023★ 11 cited

Uncertainty Aware Neural Network from Similarity and Sensitivity

H M Dipu Kabir, Subrota Kumar Mondal, Sadia Khanam +8

Researchers have proposed several approaches for neural network (NN) based uncertainty quantification (UQ). However, most of the approaches are developed considering strong assumpt…

cs.CV2023★ 9 cited

A Review of Deep Learning for Video Captioning

Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi +8

Video captioning (VC) is a fast-moving, cross-disciplinary area of research that bridges work in the fields of computer vision, natural language processing (NLP), linguistics, and…

cs.LG2023

Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing

Mehedi Hasan, Moloud Abdar, Abbas Khosravi +5

Although neural networks (especially deep neural networks) have achieved \textit{better-than-human} performance in many fields, their real-world deployment is still questionable du…

cs.LG2023

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

Behrouz Ahadzadeh, Moloud Abdar, Fatemeh Safara +3

In this paper, a new feature selection algorithm, called SFE (Simple, Fast, and Efficient), is proposed for high-dimensional datasets. The SFE algorithm performs its search process…