Deep Learning Model
Deep learning models are complex computational systems designed to learn patterns from data, achieving high accuracy in various tasks like image classification, natural language processing, and time series forecasting. Current research emphasizes improving model efficiency (e.g., through parameter reduction and optimized training algorithms), robustness (e.g., against adversarial attacks and noisy data), and interpretability (e.g., via feature attribution and visualization techniques), often employing architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs, including LSTMs and GRUs), and transformers. These advancements are driving significant impact across diverse fields, from medical diagnosis and environmental monitoring to industrial automation and personalized medicine.
Papers
A Deep Learning Model for Heterogeneous Dataset Analysis -- Application to Winter Wheat Crop Yield Prediction
Yogesh Bansal, David Lillis, Mohand Tahar Kechadi
Comparing Deep Learning Models for the Task of Volatility Prediction Using Multivariate Data
Wenbo Ge, Pooia Lalbakhsh, Leigh Isai, Artem Lensky, Hanna Suominen
Pipeline for recording datasets and running neural networks on the Bela embedded hardware platform
Teresa Pelinski, Rodrigo Diaz, Adán L. Benito Temprano, Andrew McPherson
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models
Xingying Huang
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
Yun Yi, Haokui Zhang, Rong Xiao, Nannan Wang, Xiaoyu Wang
Machine Learning for Real-Time Anomaly Detection in Optical Networks
Sadananda Behera, Tania Panayiotou, Georgios Ellinas
Catastrophic Forgetting in the Context of Model Updates
Rich Harang, Hillary Sanders
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction
Iman Deznabi, Madalina Fiterau
Prototype Learning for Explainable Brain Age Prediction
Linde S. Hesse, Nicola K. Dinsdale, Ana I. L. Namburete
Supervised Deep Learning for Content-Aware Image Retargeting with Fourier Convolutions
MohammadHossein Givkashi, MohammadReza Naderi, Nader Karimi, Shahram Shirani, Shadrokh Samavi
Frequency-Based Vulnerability Analysis of Deep Learning Models against Image Corruptions
Harshitha Machiraju, Michael H. Herzog, Pascal Frossard
A Brief Review of Hypernetworks in Deep Learning
Vinod Kumar Chauhan, Jiandong Zhou, Ping Lu, Soheila Molaei, David A. Clifton