Neural Network Model

Neural network models are computational systems inspired by the structure and function of the brain, aiming to solve complex problems through learning from data. Current research focuses on improving model interpretability (e.g., through decompilation and analysis of network weights), enhancing efficiency (e.g., via pruning and coded inference), and addressing challenges in data scarcity and security (e.g., through generative models and encrypted training). These advancements are driving progress in diverse fields, from astrophysics and materials science to finance and healthcare, by enabling more accurate predictions, efficient computations, and improved decision-making.

Papers

August 22, 2023

Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network Models
Farina Riaz, Shahab Abdulla, Hajime Suzuki, Srinjoy Ganguly, Ravinesh C. Deo, Susan Hopkins
Image Classification Development Activity Quantum Circuit Neural Network Model Multiple Physical Qubits Pre Processing

August 21, 2023

Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models
Preben M. Ness, Dusica Marijan, Sunanda Bose
Adversarial Attack Adversarial Robustness Mixed Effect Neural Network Model Causal Disentanglement Neural Causal Model Disentanglement Metric

August 9, 2023

TSSR: A Truncated and Signed Square Root Activation Function for Neural Networks
Yuanhao Gong
Neural Network Activation Function Neural Network Model Square Root

August 6, 2023

Study for Performance of MobileNetV1 and MobileNetV2 Based on Breast Cancer
Jiuqi Yan
Artificial Intelligence System Performance Study Feature Histopathological Image Neural Network Model Breast Cancer Pathology Image L MobileNet

July 24, 2023

Concept backpropagation: An Explainable AI approach for visualising learned concepts in neural network models
Patrik Hammersborg, Inga Strümke
Explainable AI Back Propagation Neural Network Model Concept Identification Explainable AI Approach Concept Learner Concept Detection

July 15, 2023

Towards Optimal Neural Networks: the Role of Sample Splitting in Hyperparameter Selection
Shijin Gong, Xinyu Zhang
Neural Network Integral Role Generalization Performance Neural Network Model Hyperparameter Selection Optimal Neural Network Cross Subject Data Splitting

July 11, 2023

Fundamental limits of overparametrized shallow neural networks for supervised learning
Francesco Camilli, Daria Tieplova, Jean Barbier
Neural Network Supervised Learning Neural Network Model Information Theoretic Two Layer Neural Network Shallow Neural Network Fundamental Limit Optimal Generalization

June 26, 2023

Methodology for generating synthetic labeled datasets for visual container inspection
Guillem Delgado, Andoni Cortés, Sara García, Estíbaliz Loyo, Maialen Berasategi, Nerea Aranjuelo
Deep Learning Deep Neural Network Data Set NCD Method Neural Network Model Large Scale Synthetic

June 22, 2023

RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness
Nicholas H. Barbara, Max Revay, Ruigang Wang, Jing Cheng, Ian R. Manchester
Machine Learning Data Driven Deep Network Neural Network Model Certified Robustness SPR Package

June 21, 2023

Wildfire Detection Via Transfer Learning: A Survey
Ziliang Hong, Emadeldeen Hamdan, Yifei Zhao, Tianxiao Ye, Hongyi Pan, A. Enis Cetin
Timely Survey Neural Network Model Wildfire Detection

June 7, 2023

Deep Learning with Partially Labeled Data for Radio Map Reconstruction
Alkesandra Malkova, Massih-Reza Amini, Benoit Denis, Christophe Villien
Deep Learning Neural Architecture Search Neural Network Model Labeled Data Radio Based Reference Signal Received Power Received Signal Strength

May 11, 2023

Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation
Niki Kiriakidou, Christos Diou
Deep Learning Causal Inference Causal Effect Neural Network Model Treatment Effect

May 10, 2023

May 6, 2023

Towards a Simple Framework of Skill Transfer Learning for Robotic Ultrasound-guidance Procedures
Tsz Yan Leung, Miguel Xochicale
Neural Network Model Robotic Ultrasound Skill Transfer

May 3, 2023

Bio-Inspired Simple Neural Network for Low-Light Image Restoration: A Minimalist Approach
Junjie Ye, Jilin Zhao
Neural Network Model Low Light Low Light Image Visual Circuit Bio Inspired Neural Network Retina Model Optical Neuron

April 22, 2023

Physics-guided generative adversarial network to learn physical models
Kazuo Yonekura
Generative Adversarial Network Physic Informed Neural Network Neural Network Model C Gan GAN Architecture Physical Model

April 1, 2023

NeuroDAVIS: A neural network model for data visualization
Chayan Maitra, Dibyendu B. Seal, Rajat K. De
High Dimensional Neural Network Model Feature Embeddings Data Visualization

March 22, 2023

Evaluating Transformer Models and Human Behaviors on Chinese Character Naming
Xiaomeng Ma, Lingyu Gao
Transformer Based Model Neural Network Model Neural Model Human Behavior Grapheme to Phoneme Definition Generation Non Semantic Speech Task

March 20, 2023

How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part II: the Multi-D Case of Two Layers with Random First Layer
Jakob Heiss, Josef Teichmann, Hanna Wutte
Neural Network Model Additive Model Generalized Additive Model Learned Function ReLU Neural Network Functional Regularization

Neural Network Model

Papers

Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network Models

Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models

TSSR: A Truncated and Signed Square Root Activation Function for Neural Networks

Study for Performance of MobileNetV1 and MobileNetV2 Based on Breast Cancer

Concept backpropagation: An Explainable AI approach for visualising learned concepts in neural network models

Towards Optimal Neural Networks: the Role of Sample Splitting in Hyperparameter Selection

Fundamental limits of overparametrized shallow neural networks for supervised learning

Methodology for generating synthetic labeled datasets for visual container inspection

RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness

Wildfire Detection Via Transfer Learning: A Survey

Deep Learning with Partially Labeled Data for Radio Map Reconstruction

Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation

Similarity of Neural Network Models: A Survey of Functional and Representational Measures

Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation

Towards a Simple Framework of Skill Transfer Learning for Robotic Ultrasound-guidance Procedures

Bio-Inspired Simple Neural Network for Low-Light Image Restoration: A Minimalist Approach

Physics-guided generative adversarial network to learn physical models

NeuroDAVIS: A neural network model for data visualization

Evaluating Transformer Models and Human Behaviors on Chinese Character Naming

How (Implicit) Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part II: the Multi-D Case of Two Layers with Random First Layer