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

October 23, 2022

Transformers For Recognition In Overhead Imagery: A Reality Check
Francesco Luzi, Aneesh Gupta, Leslie Collins, Kyle Bradbury, Jordan Malof
Deep Learning Model Transformer Megatron Decepticons Transformer Based Model Recognition Rate State of the Art Segmentation Reality Check Transformer Based Structure Overhead Imagery

October 22, 2022

Volatility forecasting using Deep Learning and sentiment analysis
V Ncume, T. L van Zyl, A Paskaramoorthy
Deep Learning Deep Learning Model Sentiment Analysis Market Volatility Volatility Forecasting

October 20, 2022

How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
Guangsheng Zhang, Bo Liu, Huan Tian, Tianqing Zhu, Ming Ding, Wanlei Zhou
Convolutional Neural Network Deep Learning Model Transformer Megatron Decepticons Privacy Policy Neural Network Architecture Privacy Risk Privacy Attack Deep Learning Technology Model Privacy

October 19, 2022

October 18, 2022

Trixi the Librarian
Fabian Wieczorek, Shang-Ching Liu, Björn Sygo, Mykhailo Koshil
Deep Learning Model Vision Pipeline Bimanual Robot Traditional Computer Vision Librarian in the Loop

October 17, 2022

October 16, 2022

October 15, 2022

Deep Regression Unlearning
Ayush K Tarun, Vikram S Chundawat, Murari Mandal, Mohan Kankanhalli
Machine Learning Deep Learning Model Machine Learning Model Unlearning Framework Deep Regression

October 13, 2022

Improving Deep Learning Models for Pediatric Low-Grade Glioma Tumors Molecular Subtype Identification Using 3D Probability Distributions of Tumor Location
Khashayar Namdar, Matthias W. Wagner, Kareem Kudus, Cynthia Hawkins, Uri Tabori, Brigit Ertl-Wagner, Farzad Khalvati
Deep Learning Model Tumor Segmentation

October 12, 2022

October 11, 2022

October 9, 2022

Using Gradient to Boost the Generalization Performance of Deep Learning Models for Fluid Dynamics
Eduardo Vital Brasil
Deep Learning Deep Learning Model Generalization Performance Natural Gradient Computational Fluid Dynamic Fluid Dynamic Performance Bottleneck Shape Optimization

October 8, 2022

The effect of variable labels on deep learning models trained to predict breast density
Steven Squires, Elaine F. Harkness, D. Gareth Evans, Susan M. Astley
Deep Learning Model Mixed Effect Variable Model Dense Label Breast Density Dense Breast

Deep Learning Model

Papers

Transformers For Recognition In Overhead Imagery: A Reality Check

Volatility forecasting using Deep Learning and sentiment analysis

How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers

Attaining Class-level Forgetting in Pretrained Model using Few Samples

Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction

Trixi the Librarian

Review Learning: Alleviating Catastrophic Forgetting with Generative Replay without Generator

An Open-source Benchmark of Deep Learning Models for Audio-visual Apparent and Self-reported Personality Recognition

Temporal-Spatial dependencies ENhanced deep learning model (TSEN) for household leverage series forecasting

Answer ranking in Community Question Answering: a deep learning approach

Comparing Synthetic Tabular Data Generation Between a Probabilistic Model and a Deep Learning Model for Education Use Cases

Deep Regression Unlearning

Improving Deep Learning Models for Pediatric Low-Grade Glioma Tumors Molecular Subtype Identification Using 3D Probability Distributions of Tumor Location

Self-Attention Message Passing for Contrastive Few-Shot Learning

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search

Improving Sample Efficiency of Deep Learning Models in Electricity Market

Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy

Deep learning model compression using network sensitivity and gradients

Using Gradient to Boost the Generalization Performance of Deep Learning Models for Fluid Dynamics

The effect of variable labels on deep learning models trained to predict breast density