Neural Network

Neural networks are computational models inspired by the structure and function of the brain, primarily aimed at approximating complex functions and solving diverse problems through learning from data. Current research emphasizes improving efficiency and robustness, exploring novel architectures like sinusoidal neural fields and hybrid models combining neural networks with radial basis functions, as well as developing methods for understanding and manipulating the internal representations learned by these networks, such as through hyper-representations of network weights. These advancements are driving progress in various fields, including computer vision, natural language processing, and scientific modeling, by enabling more accurate, efficient, and interpretable AI systems.

Papers

September 6, 2024

Calibration of Network Confidence for Unsupervised Domain Adaptation Using Estimated Accuracy
Coby Penso, Jacob Goldberger
Neural Network Domain Adaptation Calibration Performance Calibration Method Prediction Confidence Accuracy Estimation
FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems
Franziska Griese, Fabian Hoppe, Alexander Rüttgers, Philipp Knechtges
Neural Network Inverse Problem Fluid Dynamic Data Discretization Navier Stokes Machine Learning Regression Incompressible Fluid

September 5, 2024

WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking
Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri, Enzo Tartaglione
Neural Network Deep Neural Network
Memory-Optimized Once-For-All Network
Maxime Girard, Victor Quétu, Samuel Tardieu, Van-Tam Nguyen, Enzo Tartaglione
Neural Network Neural Architecture Search Memory Efficient Fit All Approach
Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron
Christian Schmid, James M. Murray
Reinforcement Learning Neural Network Learning Dynamic Learning Rule Elementary Perceptron
Reducing Bias in Deep Learning Optimization: The RSGDM Approach
Honglin Qin, Hongye Zheng, Bingxing Wang, Zhizhong Wu, Bingyao Liu, Yuanfang Yang
Neural Network Stochastic Gradient Descent Learning Rate SGDA Algorithm Fast AltGDA Type Algorithm
Shuffle Vision Transformer: Lightweight, Fast and Efficient Recognition of Driver Facial Expression
Ibtissam Saadi, Douglas W. Cunningham, Taleb-ahmed Abdelmalik, Abdenour Hadid, Yassin El Hillali
Neural Network Convolutional Neural Network Vision Transformer Facial Expression Image Recognition Lightweight High Expression Recognition
Weight Conditioning for Smooth Optimization of Neural Networks
Hemanth Saratchandran, Thomas X. Wang, Simon Lucey
Neural Network Consistent Conditioning Normalization Technique Model Precondition Smooth Optimization Unified Normalization Face Normalization Neural Network Weight Matrix

September 4, 2024

Hyperbolic Brain Representations
Alexander Joseph, Nathan Francis, Meijke Balay
Neural Network Artificial Intelligence Human Brain Hyperbolic Representation Hyperbolic Neural Network Latent Geometry
Boundless: Generating Photorealistic Synthetic Data for Object Detection in Urban Streetscapes
Mehmet Kerem Turkcan, Yuyang Li, Chengbo Zang, Javad Ghaderi, Gil Zussman, Zoran Kostic
Neural Network Synthetic Data Object Detection Object Detection Model Ground Truth Annotation
SNNAX -- Spiking Neural Networks in JAX
Jamie Lohoff, Jan Finkbeiner, Emre Neftci
Neural Network Spiking Neural Network Neuromorphic Hardware State of the Art JAX
Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon
Ramon Tavares, Ricardo Olinda
Neural Network Recurrent Neural Network Long Short Term Memory Gated Recurrent Unit Target Amazon Ally Extreme Weather Wildfire Forecasting

September 3, 2024

K-Origins: Better Colour Quantification for Neural Networks
Lewis Mason, Mark Martinez
Neural Network Semantic Segmentation Receptive Field Encoder Decoder Visual Creation
GradINN: Gradient Informed Neural Network
Filippo Aglietti, Francesco Della Santa, Andrea Piano, Virginia Aglietti
Neural Network Physic Informed Neural Network Gradient Based Governing Equation
Decoding finger velocity from cortical spike trains with recurrent spiking neural networks
Tengjun Liu, Julia Gygax, Julian Rossbroich, Yansong Chua, Shaomin Zhang, Friedemann Zenke
Neural Network Neuromorphic Hardware Spike Train Finger Motion Brain Machine Interface
Frequency-Spatial Entanglement Learning for Camouflaged Object Detection
Yanguang Sun, Chunyan Xu, Jian Yang, Hanyu Xuan, Lei Luo
Neural Network Vision Transformer Camouflaged Object Detection
AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling
Siddhant Dutta, Nouhaila Innan, Sadok Ben Yahia, Muhammad Shafique
Neural Network Physic Informed Neural Network Self Attention Tensor Network Climate Model Variational Quantum Quantum Hard Attention
DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection
Weichao Pan, Jiaju Kang, Xu Wang, Zhihao Chen, Yiyuan Ge
Neural Network Dual Attention Street Level Road Damage Detection
Quantifying Emergence in Neural Networks: Insights from Pruning and Training Dynamics
Faisal AlShinaifi, Zeyad Almoaigel, Johnny Jingze Li, Abdulla Kuleib, Gabriel A. Silva
Neural Network DCU Insight AQ Edge Pruning Path Breaking Emergence Training Dynamic Emergent Behavior Complex Behavior Quantifying Emergence
Hybridization of Persistent Homology with Neural Networks for Time-Series Prediction: A Case Study in Wave Height
Zixin Lin, Nur Fariha Syaqina Zulkepli, Mohd Shareduwan Mohd Kasihmuddin, R. U. Gobithaasan
Neural Network Recurrent Neural Network Long Short Term Memory Topological Feature Persistent Homology Time Series Prediction Significant Wave Height

Neural Network

Papers

Calibration of Network Confidence for Unsupervised Domain Adaptation Using Estimated Accuracy

FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems

WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking

Memory-Optimized Once-For-All Network

Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron

Reducing Bias in Deep Learning Optimization: The RSGDM Approach

Shuffle Vision Transformer: Lightweight, Fast and Efficient Recognition of Driver Facial Expression

Weight Conditioning for Smooth Optimization of Neural Networks

Hyperbolic Brain Representations

Boundless: Generating Photorealistic Synthetic Data for Object Detection in Urban Streetscapes

SNNAX -- Spiking Neural Networks in JAX

Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon

K-Origins: Better Colour Quantification for Neural Networks

GradINN: Gradient Informed Neural Network

Decoding finger velocity from cortical spike trains with recurrent spiking neural networks

Frequency-Spatial Entanglement Learning for Camouflaged Object Detection

AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling

DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection

Quantifying Emergence in Neural Networks: Insights from Pruning and Training Dynamics

Hybridization of Persistent Homology with Neural Networks for Time-Series Prediction: A Case Study in Wave Height