Deep Learning

Deep learning, a subfield of machine learning, focuses on training artificial neural networks with multiple layers to extract complex patterns from data. Current research emphasizes improving model robustness against noisy or adversarial inputs, exploring efficient architectures like Vision Transformers and convolutional LSTMs for various tasks (e.g., image classification, time series forecasting), and integrating physics-informed approaches for enhanced interpretability and reliability. These advancements are significantly impacting diverse fields, from automated industrial inspection and medical image analysis to improved weather forecasting and more efficient content moderation systems.

3874papers

Papers - Page 41

September 17, 2024

Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling
Lukas Schynol, Marius Pesavento
Network Programming Deep Unrolling Deep Learning Deep Learning Architecture Tensor Decomposition Anomaly Detection
Golden Ratio Search: A Low-Power Adversarial Attack for Deep Learning based Modulation Classification
Deepsayan Sadhukhan, Nitin Priyadarshini Shankar, Sheetal Kalyani
Deep Learning Automatic Modulation Classification Adversarial Attack Modulation Classification Adversarial Training Attack Strategy

September 15, 2024

Recent advances in deep learning and language models for studying the microbiome
Binghao Yan, Yunbi Nam, Lingyao Li, Rebecca A. Deek, Hongzhe Li, Siyuan Ma
Recent Advance Microbiome Datasets Microbiome Research Deep Learning Language Model
Enhancing Lesion Segmentation in PET/CT Imaging with Deep Learning and Advanced Data Preprocessing Techniques
Jiayi Liu, Qiaoyi Xue, Youdan Feng, Tianming Xu, Kaixin Shen, Chuyun Shen, Yuhang Shi
Augmentation Pipeline Deep Learning PET Dog Whole Body Computed Tomography Preprocessing Method Data Preprocessing

September 14, 2024

Deep Learning Under Siege: Identifying Security Vulnerabilities and Risk Mitigation Strategies
Jamal Al-Karaki, Muhammad Al-Zafar Khan, Mostafa Mohamad, Dababrata Chowdhury
Deep Learning Technology Security Vulnerability Military Application Deep Learning Artificial Intelligence Security Challenge
A Dynamic Weighting Strategy to Mitigate Worker Node Failure in Distributed Deep Learning
Yuesheng Xu, Arielle Carr
Weighting Strategy Straggler Mitigation Convergence Rate Distributed Learning Deep Learning Critical Node Stochastic Gradient Descent Dynamic Weighting

September 13, 2024

Are Sparse Neural Networks Better Hard Sample Learners?
Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu
Sparse Neural Network Deep Learning Dense Model Deep Neural Network
PINNfluence: Influence Functions for Physics-Informed Neural Networks
Jonas R. Naujoks, Aleksander Krasowski, Moritz Weckbecker, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek, René P. Klausen
Deep Learning Physic Informed Neural Network Fluid Flow Reg PINNs Partial Differential Equation Influence Function
Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems
Altaf Allah Abbassi, Houssem Ben Braiek, Foutse Khomh, Thomas Reid
Quality Inspection Variational Auto Rule Based High Quality Risk Description Deep Learning Visual Inspection Vision Based Industrial Inspection Continual Training
Recent Trends in Modelling the Continuous Time Series using Deep Learning: A Survey
Mansura Habiba, Barak A. Pearlmutter, Mehrdad Maleki
Recent Trend Time Series Timely Survey Continuous Variable Deep Learning
Task-Specific Data Preparation for Deep Learning to Reconstruct Structures of Interest from Severely Truncated CBCT Data
Yixing Huang, Fuxin Fan, Ahmed Gomaa, Andreas Maier, Rainer Fietkau, Christoph Bert, Florian Putz
Cone Beam Computed Tomography Cone Beam Computed Tomography Data Simple Structure Deep Learning Data Preparation

September 12, 2024

COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning
Zian Wang, Xinyi Lu
Econometric Model Stochastic Volatility Volatility Forecasting GARCH Model Deep Learning
Digital Volumetric Biopsy Cores Improve Gleason Grading of Prostate Cancer Using Deep Learning
Ekaterina Redekop, Mara Pleasure, Zichen Wang, Anthony Sisk, Yang Zong, Kimberly Flores, William Speier, Corey W. Arnold
Pathology Image Gleason Grade Deep Learning Deep Feature Biopsy Core Prostate Cancer
Deep Multimodal Learning with Missing Modality: A Survey
Renjie Wu, Hu Wang, Hsiang-Ting Chen, Gustavo Carneiro
Comprehensive Survey Multimodal Learning Multimodal Deep Learning Deep Learning Missing Modality

September 11, 2024

Deep Learning of Dynamic Systems using System Identification Toolbox(TM)
Tianyu Dai, Khaled Aljanaideh, Rong Chen, Rajiv Singh, Alec Stothert, Lennart Ljung
System Identification Deep Learning Nonlinear Model Neural State Space Model Reduced Order Dynamic Modeling
Deep Learning for predicting rate-induced tipping
Yu Huang, Sebastian Bathiany, Peter Ashwin, Niklas Boers
Tipping Point Dynamic Shift Deep Learning
KKT-Informed Neural Network
Carmine Delle Femine
Optimality Criterion Optimization Problem Deep Learning Neural Network Based Convex Optimization

Deep Learning

Papers - Page 41

Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling

Golden Ratio Search: A Low-Power Adversarial Attack for Deep Learning based Modulation Classification

On the effects of similarity metrics in decentralized deep learning under distributional shift

TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering

Research and Design of a Financial Intelligent Risk Control Platform Based on Big Data Analysis and Deep Machine Learning

Recent advances in deep learning and language models for studying the microbiome

Enhancing Lesion Segmentation in PET/CT Imaging with Deep Learning and Advanced Data Preprocessing Techniques

Deep Learning Under Siege: Identifying Security Vulnerabilities and Risk Mitigation Strategies

A Dynamic Weighting Strategy to Mitigate Worker Node Failure in Distributed Deep Learning

Are Sparse Neural Networks Better Hard Sample Learners?

PINNfluence: Influence Functions for Physics-Informed Neural Networks

Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems

Recent Trends in Modelling the Continuous Time Series using Deep Learning: A Survey

Task-Specific Data Preparation for Deep Learning to Reconstruct Structures of Interest from Severely Truncated CBCT Data

COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning

Digital Volumetric Biopsy Cores Improve Gleason Grading of Prostate Cancer Using Deep Learning

Deep Multimodal Learning with Missing Modality: A Survey

Deep Learning of Dynamic Systems using System Identification Toolbox(TM)

Deep Learning for predicting rate-induced tipping

KKT-Informed Neural Network