Latest Articles for Activation Functions

Machine Learning Insights into Shallow Neural Networks

A deep look into the characteristics and training of two-layer neural networks.

2025-09-22T19:39:12+00:00 ― 6 min read

Machine Learning Advances in Neural Network Training and Regularization

A look into improving neural networks through optimization and training techniques.

2025-09-22T02:07:48+00:00 ― 8 min read

Machine Learning Neural Networks and Hypercomplex Numbers

Exploring the role of hypercomplex-valued neural networks in modern applications.

2025-09-18T22:34:54+00:00 ― 5 min read

Machine Learning Minimum Width in Deep Neural Networks

Research reveals new insights on the minimum width for effective neural networks.

2025-09-18T12:53:32+00:00 ― 6 min read

Machine Learning Insights into Two-Layer Neural Networks

This study reveals key factors influencing neural network training and performance.

2025-09-17T14:36:29+00:00 ― 5 min read

Machine Learning Understanding the Role of the Hessian in Model Learning

Explore how the Hessian impacts machine learning model performance and training strategies.

2025-09-15T21:46:12+00:00 ― 7 min read

Software Engineering Assessing Trustworthiness in Deep Learning Model Predictions

A new method for evaluating deep learning model reliability using data preconditions.

2025-09-14T13:07:00+00:00 ― 5 min read

Machine Learning Introducing Positive Concave Deep Equilibrium Models

A new approach to deep learning that improves efficiency and stability.

2025-09-10T13:07:54+00:00 ― 8 min read

Machine Learning ApiQ: Advancing Memory-Efficient Fine-Tuning for LLMs

Introducing ApiQ for improved fine-tuning and quantization of large language models.

2025-09-10T01:32:42+00:00 ― 6 min read

Machine Learning Improving Sampling Methods in Bayesian Neural Networks

This article discusses methods to enhance sampling efficiency in Bayesian neural networks.

2025-09-06T21:28:40+00:00 ― 5 min read

Dynamical Systems New Neural Network Approach for Predicting Periodic Behaviors

This study presents a neural network designed to understand periodic systems.

2025-09-05T13:47:16+00:00 ― 5 min read

Machine Learning Adaptive Activation Functions: Enhancing Neural Networks with Limited Data

This study investigates adaptive activation functions for improved model performance in low data scenarios.

2025-09-04T01:53:16+00:00 ― 6 min read

Machine Learning Exploring Memory Capacity in Neural Networks

An overview of memory capacity in wide treelike committee machines and its implications.

2025-09-03T08:21:52+00:00 ― 5 min read

Machine Learning The Complex Simplicity of Neural Networks

Examining how neural networks prioritize simpler functions over complex patterns.

2025-09-01T17:56:18+00:00 ― 6 min read

Machine Learning Improving Efficiency in Low-Precision Neural Networks

This paper discusses the costs and improvements for low-precision neural networks.

2025-08-24T09:16:42+00:00 ― 4 min read

Fluid Dynamics Advances in Fluid Dynamics Using Machine Learning

Research shows promise in using AI to improve fluid flow predictions.

2025-08-20T19:30:36+00:00 ― 5 min read

Machine Learning Physics-Informed Neural Networks: A New Approach

Learn how PINNs combine machine learning and physics to solve complex problems.

2025-08-14T06:29:06+00:00 ― 6 min read

Computational Engineering, Finance, and Science Neural Networks in Duct Acoustics: A New Approach

This article examines how neural networks predict sound behavior in ducts.

2025-08-13T02:18:30+00:00 ― 6 min read

Machine Learning The Role of Lazy Training in Neural Networks

Exploring how lazy training impacts neural network performance and learning dynamics.

2025-08-12T14:50:12+00:00 ― 6 min read

Machine Learning Improving Machine Classification with Contextual Information

A new method enhances image classification accuracy by focusing on context.

2025-08-10T01:14:00+00:00 ― 5 min read

Optimization and Control Training Monotonic Neural Networks for Image Processing

A new method ensures reliable image restoration by training monotonic neural networks.

2025-08-08T00:39:32+00:00 ― 6 min read

Machine Learning Advancements in Machine Learning with KANs

Kolmogorov-Arnold Networks offer innovative solutions for data analysis and learning.

2025-08-06T01:07:36+00:00 ― 6 min read

Machine Learning Neural Tangent Kernel: Key to Effective Learning

This study highlights the significance of the Neural Tangent Kernel in training neural networks.

2025-08-02T11:23:27+00:00 ― 5 min read

Computer Vision and Pattern Recognition MetaMixer: A New Approach to Data Processing

Discover how MetaMixer transforms model efficiency and adaptability.

2025-08-02T08:14:30+00:00 ― 6 min read

Machine Learning Advancements in Sparse Autoencoders for Language Models

This article explores improvements in sparse autoencoders and their impact on language understanding.

2025-08-01T09:19:54+00:00 ― 7 min read

Numerical Analysis Addressing Discretization Error in Fourier Neural Operators

Analyzing and mitigating discretization errors in Fourier Neural Operators for better predictions.

2025-07-29T19:33:54+00:00 ― 6 min read

Machine Learning Analyzing Separation Power in Equivariant Neural Networks

A look into how equivariant networks distinguish between inputs effectively.

2025-07-29T04:42:06+00:00 ― 6 min read

Machine Learning Advancements in Surrogate Gradient Learning for Neural Networks

A study on improving neural network training with non-differentiable activation functions.

2025-07-27T05:48:48+00:00 ― 6 min read

Statistical Mechanics The Impact of Noise on Transport Networks

Analyzing how noise influences the efficiency of transport systems.

2025-07-23T09:02:00+00:00 ― 7 min read

Machine Learning The Evolving Role of RNNs in Temporal Point Processes

An analysis of RNN-TPPs and their impact on event prediction accuracy.

2025-07-21T06:17:20+00:00 ― 7 min read

Machine Learning SineKAN: A New Era in Neural Networks

SineKAN offers improved speed and performance using sine functions in neural networks.

2025-07-19T14:48:42+00:00 ― 4 min read

Machine Learning The Mechanics of Neural Networks

A clear look at how neural networks work and their significance in data representation.

2025-07-14T22:24:15+00:00 ― 5 min read

Machine Learning Introducing DropKAN: A New Approach for KANs

DropKAN improves KANs' performance by addressing Dropout issues.

2025-07-12T00:27:12+00:00 ― 5 min read

Machine Learning Introducing PSVAE: A New Approach to Synthetic Data Generation

PSVAE offers a faster method for creating high-quality synthetic tabular data.

2025-07-11T23:47:42+00:00 ― 5 min read

General Economics Deep Learning's Role in Economic Analysis

Discover how deep learning aids economists in analyzing complex data.

2025-07-11T04:29:02+00:00 ― 5 min read

Machine Learning Comparing Kolmogorov–Arnold Networks and Multi-Layer Perceptrons

A look at the strengths and weaknesses of KANs and MLPs in machine learning.

2025-07-08T09:41:06+00:00 ― 5 min read

Hardware Architecture Understanding Convolutional Neural Networks in AI

A guide to how CNNs enhance image processing and recognition.

2025-07-06T21:04:54+00:00 ― 5 min read

Artificial Intelligence Advancing Neural Networks with Graded Vector Spaces

A new approach to improve neural networks using graded vector spaces.

2025-07-06T15:09:24+00:00 ― 5 min read

Neural and Evolutionary Computing CAReLU: A Shift in Activation Functions

CAReLU enhances learning by balancing positive and negative values in deep learning models.

2025-07-05T20:59:12+00:00 ― 5 min read

Machine Learning Improving Kolmogorov-Arnold Networks with Averaging

Averaging enhances KANs' performance and stability in machine learning tasks.

2025-07-04T19:42:24+00:00 ― 6 min read