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.

Papers

October 12, 2024

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health
Abdullah Mamun, Lawrence D. Devoe, Mark I. Evans, David W. Britt, Judith Klein-Seetharaman, Hassan Ghasemzadeh
Deep Learning Greater Public Use Artificial Intelligence Model Risk Factor Neonatal Outcome
Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques
Pohsun Feng, Ziqian Bi, Yizhu Wen, Benji Peng, Junyu Liu, Caitlyn Heqi Yin, Tianyang Wang, Keyu Chen, Sen Zhang, Ming Li, Jiawei Xu, Ming Liu, Xuanhe Pan, Jinlang Wang, Qian Niu
Language Model Deep Learning Machine Learning Big Data Online autoML AutoML Tool Auto Sklearn
Improving 3D Finger Traits Recognition via Generalizable Neural Rendering
Hongbin Xu, Junduan Huang, Yuer Ma, Zifeng Li, Wenxiong Kang
Deep Learning 3D Reconstruction High Quality Rendering 3D Fingerprint

October 11, 2024

Learning Algorithms Made Simple
Noorbakhsh Amiri Golilarz, Elias Hossain, Abdoljalil Addeh, Keyan Alexander Rahimi
Deep Learning Machine Learning Convolutional Neural Network Learning Algorithm
HyperPg -- Prototypical Gaussians on the Hypersphere for Interpretable Deep Learning
Maximilian Xiling Li, Korbinian Franz Rudolf, Nils Blank, Rudolf Lioutikov
Deep Learning
Multi-modal Fusion based Q-distribution Prediction for Controlled Nuclear Fusion
Shiao Wang, Yifeng Wang, Qingchuan Ma, Xiao Wang, Ning Yan, Qingquan Yang, Guosheng Xu, Jin Tang
Deep Learning Multimodal Fusion Multi Modal Fusion Nuclear Fusion

October 10, 2024

Bilinear MLPs enable weight-based mechanistic interpretability
Michael T. Pearce, Thomas Dooms, Alice Rigg, Jose M. Oramas, Lee Sharkey
Deep Learning Mechanistic Interpretability Bilinear Convolutional Neural Network MLP Layer
Optimizing YOLO Architectures for Optimal Road Damage Detection and Classification: A Comparative Study from YOLOv7 to YOLOv10
Vung Pham, Lan Dong Thi Ngoc, Duy-Linh Bui
Deep Learning Classification Code YOLOv5 Model YOLO Model Road Scene Road Damage Road Damage Detection
Physics and Deep Learning in Computational Wave Imaging
Youzuo Lin, Shihang Feng, James Theiler, Yinpeng Chen, Umberto Villa, Jing Rao, John Greenhall, Cristian Pantea, Mark A. Anastasio, Brendt Wohlberg
Deep Learning Theoretical Physic Computational Imaging Wave Propagation Acoustic Imaging
Deep Learning for Generalised Planning with Background Knowledge
Dillon Z. Chen, Rostislav Horčík, Gustav Šír
Deep Learning Reasoning Capability Background Knowledge Classical Planning Generalized Planning
Exploring Foundation Models in Remote Sensing Image Change Detection: A Comprehensive Survey
Zihan Yu, Tianxiao Li, Yuxin Zhu, Rongze Pan
Deep Learning Foundation Model Comprehensive Survey Remote Sensing Change Detection Information Fusion
On the Generalization Properties of Deep Learning for Aircraft Fuel Flow Estimation Models
Gabriel Jarry, Ramon Dalmau, Philippe Very, Junzi Sun
Deep Learning Model Generalization Generalization Property Fuel Consumption
Boosting Deep Ensembles with Learning Rate Tuning
Hongpeng Jin, Yanzhao Wu
Deep Learning Learning Rate Deep Ensemble

October 9, 2024

Exploring the design space of deep-learning-based weather forecasting systems
Shoaib Ahmed Siddiqui, Jean Kossaifi, Boris Bonev, Christopher Choy, Jan Kautz, David Krueger, Kamyar Azizzadenesheli
Deep Learning Design Space Convolutional Architecture Grid Based
Enhancing Soccer Camera Calibration Through Keypoint Exploitation
Nikolay S. Falaleev, Ruilong Chen
Deep Learning Camera Calibration
JPEG Inspired Deep Learning
Ahmed H. Salamah, Kaixiang Zheng, Yiwen Liu, En-Hui Yang
Deep Learning Joint Photographic Expert Group
Emergent properties with repeated examples
François Charton, Julia Kempe
Deep Learning Strong Generalization Fewer Example Fast Learning Emergent Property

Deep Learning

Papers

Towards Reproducible Learning-based Compression

TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis

Distributed Intelligent Video Surveillance for Early Armed Robbery Detection based on Deep Learning

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health

Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques

Improving 3D Finger Traits Recognition via Generalizable Neural Rendering

Learning Algorithms Made Simple

HyperPg -- Prototypical Gaussians on the Hypersphere for Interpretable Deep Learning

Multi-modal Fusion based Q-distribution Prediction for Controlled Nuclear Fusion

Bilinear MLPs enable weight-based mechanistic interpretability

Optimizing YOLO Architectures for Optimal Road Damage Detection and Classification: A Comparative Study from YOLOv7 to YOLOv10

Physics and Deep Learning in Computational Wave Imaging

Deep Learning for Generalised Planning with Background Knowledge

Exploring Foundation Models in Remote Sensing Image Change Detection: A Comprehensive Survey

On the Generalization Properties of Deep Learning for Aircraft Fuel Flow Estimation Models

Boosting Deep Ensembles with Learning Rate Tuning

Exploring the design space of deep-learning-based weather forecasting systems

Enhancing Soccer Camera Calibration Through Keypoint Exploitation

JPEG Inspired Deep Learning

Emergent properties with repeated examples