Ai alignment: A comprehensive survey
AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …
Machine Learning, Deep Learning and Statistical Analysis for forecasting building energy consumption—A systematic review
The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …
A simple and effective pruning approach for large language models
As their size increases, Large Languages Models (LLMs) are natural candidates for network
pruning methods: approaches that drop a subset of network weights while striving to …
pruning methods: approaches that drop a subset of network weights while striving to …
b-darts: Beta-decay regularization for differentiable architecture search
Abstract Neural Architecture Search (NAS) has attracted increasingly more attention in
recent years because of its capability to design deep neural network automatically. Among …
recent years because of its capability to design deep neural network automatically. Among …
Covid-transformer: Interpretable covid-19 detection using vision transformer for healthcare
In the recent pandemic, accurate and rapid testing of patients remained a critical task in the
diagnosis and control of COVID-19 disease spread in the healthcare industry. Because of …
diagnosis and control of COVID-19 disease spread in the healthcare industry. Because of …
Large separable kernel attention: Rethinking the large kernel attention design in cnn
Abstract Visual Attention Networks (VAN) with Large Kernel Attention (LKA) modules have
been shown to provide remarkable performance, that surpasses Vision Transformers (ViTs) …
been shown to provide remarkable performance, that surpasses Vision Transformers (ViTs) …
DNoiseNet: Deep learning-based feedback active noise control in various noisy environments
YJ Cha, A Mostafavi, SS Benipal - Engineering Applications of Artificial …, 2023 - Elsevier
The use of active noise control/cancelation (ANC) has increased because of the availability
of efficient circuits and computational power. However, most ANC systems are based on …
of efficient circuits and computational power. However, most ANC systems are based on …
Automatic concrete crack segmentation model based on transformer
W Wang, C Su - Automation in Construction, 2022 - Elsevier
Routine visual inspection of concrete structures is essential to maintain safe conditions.
Therefore, studies of concrete crack segmentation using deep learning methods have been …
Therefore, studies of concrete crack segmentation using deep learning methods have been …
Learning from teaching regularization: Generalizable correlations should be easy to imitate
Generalization remains a central challenge in machine learning. In this work, we propose
Learning from Teaching (LoT), a novel regularization technique for deep neural networks to …
Learning from Teaching (LoT), a novel regularization technique for deep neural networks to …
Coaid-deep: An optimized intelligent framework for automated detecting covid-19 misleading information on twitter
COVID-19 has affected all peoples' lives. Though COVID-19 is on the rising, the existence of
misinformation about the virus also grows in parallel. Additionally, the spread of …
misinformation about the virus also grows in parallel. Additionally, the spread of …