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Popular Articles Alert for this Publication# 34
Site URL: ieeexplore.ieee.org
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Deep Time Series Models: A Comprehensive Survey and Benchmark
http://ieeexplore.ieee.org/document/11509648
Published: May 6, 2026 13:20
Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other data modalities, time series present unique challenges in learning and modeling due to their intricate and…
Diving Into Epipolar Transformers for Light Field Super-Resolution and Disparity Estimation
http://ieeexplore.ieee.org/document/11440142
Published: March 17, 2026 13:21
Light field (LF) cameras capture the light rays of a 3D scene from multiple views simultaneously, and thus provide a more immersive experience of the real world as compared to traditional cameras. Although significant progress has been made in various LF…
StarIR: Convolutional Image Restoration With Spatial-Frequency Fusion
http://ieeexplore.ieee.org/document/11429607
Published: March 10, 2026 13:16
Vision Transformer (ViT) has shown impressive performance in image restoration due to its ability to capture a large receptive field. However, its complexity grows quadratically with input resolution, limiting its applicability for high-resolution images.…
Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment
http://ieeexplore.ieee.org/document/11364256
Published: January 26, 2026 13:18
With the continuous growth in the number of parameters of the Transformer-based pretrained language models (PLMs), particularly the emergence of large language models (LLMs) with billions of parameters, many natural language processing (NLP) tasks have…
A Review of Uncertainty Representation and Quantification in Neural Networks
http://ieeexplore.ieee.org/document/11219221
Published: October 28, 2025 13:17
Effectively estimating the uncertainty attached to neural network predictions thus becomes essential to improve robustness, reliability, and trustworthiness. This paper provides an overview of various methodologies for representing, quantifying, and…
A Comprehensive Survey on Evidential Deep Learning and its Applications
http://ieeexplore.ieee.org/document/11217233
Published: October 24, 2025 13:16
Reliable uncertainty estimation has become a crucial requirement for the industrial deployment of deep learning algorithms, particularly in high-risk applications such as autonomous driving and medical diagnosis. However, uncertainty estimation methods…