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

February 6, 2024

Tabular Data: Is Attention All You Need?
Guri Zabërgja, Arlind Kadra, Josif Grabocka
Neural Network Deep Learning Human Attention Tabular Data Tabular Datasets
AttackNet: Enhancing Biometric Security via Tailored Convolutional Neural Network Architectures for Liveness Detection
Oleksandr Kuznetsov, Dmytro Zakharov, Emanuele Frontoni, Andrea Maranesi
Deep Learning Adversarial Attack Biometric System Biometric Verification Liveness Detection

February 5, 2024

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian Foster
Deep Learning Timely Survey Technical Challenge Vision Paper Scientific Discovery Billion Parameter
Discovering interpretable models of scientific image data with deep learning
Christopher J. Soelistyo, Alan R. Lowe
Deep Learning Representation Learning Interpretable Model Microscopy Image Scientific Image Scientific Explanation
Data-induced multiscale losses and efficient multirate gradient descent schemes
Juncai He, Liangchen Liu, Yen-Hsi Richard Tsai
Deep Learning Gradient Descent Multi Scale Multiscale Structure Benchmark Multiscale System
Toward Green and Human-Like Artificial Intelligence: A Complete Survey on Contemporary Few-Shot Learning Approaches
Georgios Tsoumplekas, Vladislav Li, Vasileios Argyriou, Anastasios Lytos, Eleftherios Fountoukidis, Sotirios K. Goudos, Ioannis D. Moscholios, Panagiotis Sarigiannidis
Deep Learning LeArning Abstract Comprehensive Survey Fast Adaptation Learning Task Learning Approach CLASSIC Modern Contemporary
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation
Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong
Deep Learning Recommendation Model New Paradigm Recommendation Quality Dynamic Sparse Training
Deep Nonlinear Hyperspectral Unmixing Using Multi-task Learning
Saeid Mehrdad, Seyed AmirHossein Janani
Deep Learning Multi Task Learning Hyperspectral Image Nonlinear Model Hidden Layer Hyperspectral Unmixing

February 3, 2024

SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach
Tianshi Wang, Jinyang Li, Ruijie Wang, Denizhan Kara, Shengzhong Liu, Davis Wertheimer, Antoni Viros-i-Martin, Raghu Ganti, Mudhakar Srivatsa, Tarek Abdelzaher
Deep Learning Deep Learning Model Synthetic Data Internet of Thing Generative Approach Generative Framework Neural Network Robustness
Diabetes detection using deep learning techniques with oversampling and feature augmentation
María Teresa García-Ordás, Carmen Benavides, José Alberto Benítez-Andrades, Héctor Alaiz-Moretón, Isaías García-Rodríguez
Deep Learning Convolutional Neural Network Barzilai Borwein Technique Feature Augmentation Type 2 Diabetes Oversampling Method
Enhancing crop classification accuracy by synthetic SAR-Optical data generation using deep learning
Ali Mirzaei, Hossein Bagheri, Iman Khosravi
Deep Learning Generative Adversarial Network Training Data Crop Classification SAR to Optical
Transfer Learning in ECG Diagnosis: Is It Effective?
Cuong V. Nguyen, Cuong D. Do
Deep Learning Deep Neural Network Transfer Learning Multi Label ECG Analysis ECG Datasets

February 2, 2024

Predicting ATP binding sites in protein sequences using Deep Learning and Natural Language Processing
Shreyas V, Swati Agarwal
Deep Learning Natural Language Processing BERT Model Protein Sequence LightGBM Model Multiple Embeddings Multi Site Adenosine Triphosphate
Location Agnostic Adaptive Rain Precipitation Prediction using Deep Learning
Md Shazid Islam, Md Saydur Rahman, Md Saad Ul Haque, Farhana Akter Tumpa, Md Sanzid Bin Hossain, Abul Al Arabi
Deep Learning Deep Neural Network Adaptation Concern Precipitation Prediction Climate Pattern Precipitation Forecasting Adaptive Deep
Recent Advances in Predictive Modeling with Electronic Health Records
Jiaqi Wang, Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Aofei Chang, Guanjie Huang, Ziyi Yin, Cao Xiao, Jimeng Sun, Fenglong Ma
Deep Learning Electronic Health Record Predictive Model Recent Advance Electronic Health Record Data

February 1, 2024

Enhanced fringe-to-phase framework using deep learning
Won-Hoe Kim, Bongjoong Kim, Hyung-Gun Chi, Jae-Sang Hyun
Deep Learning Structured Light Symmetric Neural Network Fringe Projection Fringe Pattern

Deep Learning

Papers

Tabular Data: Is Attention All You Need?

AttackNet: Enhancing Biometric Security via Tailored Convolutional Neural Network Architectures for Liveness Detection

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision

Discovering interpretable models of scientific image data with deep learning

Data-induced multiscale losses and efficient multirate gradient descent schemes

Toward Green and Human-Like Artificial Intelligence: A Complete Survey on Contemporary Few-Shot Learning Approaches

Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation

Deep Nonlinear Hyperspectral Unmixing Using Multi-task Learning

Classification of Tennis Actions Using Deep Learning

On the Role of Initialization on the Implicit Bias in Deep Linear Networks

A Collaborative Model-driven Network for MRI Reconstruction

NetLLM: Adapting Large Language Models for Networking

SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach

Diabetes detection using deep learning techniques with oversampling and feature augmentation

Enhancing crop classification accuracy by synthetic SAR-Optical data generation using deep learning

Transfer Learning in ECG Diagnosis: Is It Effective?

Predicting ATP binding sites in protein sequences using Deep Learning and Natural Language Processing

Location Agnostic Adaptive Rain Precipitation Prediction using Deep Learning

Recent Advances in Predictive Modeling with Electronic Health Records

Enhanced fringe-to-phase framework using deep learning