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

May 30, 2024

Optimizing cnn-Bigru performance: Mish activation and comparative analysis with Relu
Asmaa Benchama, Khalid Zebbara
Neural Network Deep Learning Comparative Study Intrusion Detection System ReLU Layer CNN Performance Capturing Extreme Activation
Recurrent neural network wave functions for Rydberg atom arrays on kagome lattice
Mohamed Hibat-Allah, Ejaaz Merali, Giacomo Torlai, Roger G Melko, Juan Carrasquilla
Neural Network Recurrent Event Spin Lattice Rydberg Atom Square Lattice
Flexible SE(2) graph neural networks with applications to PDE surrogates
Maria Bånkestad, Olof Mogren, Aleksis Pirinen
Neural Network Financial Application Inter Part Equivariance Equivariant Model Neural PDE Flow Simulation
Tropical Expressivity of Neural Networks
Paul Lezeau, Thomas Walker, Yueqi Cao, Shiv Bhatia, Anthea Monod
Neural Network Algebraic Framework Tropical Geometry
Symmetries in Overparametrized Neural Networks: A Mean-Field View
Javier Maass, Joaquin Fontbona
Neural Network Mean Field Learning Dynamic Approximate Symmetry Shallow Neural Network Symmetric Model
Semantic Landmark Detection & Classification Using Neural Networks For 3D In-Air Sonar
Wouter Jansen, Jan Steckel
Neural Network Classification Code Autonomous Navigation Simultaneous Localization Autonomous Navigation System Semantic Landmark Detection 3D Sonar

May 29, 2024

Understanding and Minimising Outlier Features in Neural Network Training
Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann
Neural Network Human Understanding Training Dynamic Neuron Activation Outlier Removal Outlier Event Outlier Explanation
Convex neural network synthesis for robustness in the 1-norm
Ross Drummond, Chris Guiver, Matthew C. Turner
Neural Network Native Robustness Predictive Control Semi Structured Neural Network Robustness Accuracy Trade
Few-Shot Testing: Estimating Uncertainty of Memristive Deep Neural Networks Using One Bayesian Test Vector
Soyed Tuhin Ahmed, Mehdi Tahoori
Neural Network High Uncertainty Anticipation Level Test Memristive Device Computing in Memory
Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization
Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong, Xin Yao, Ke Tang
Neural Network LeArning Abstract Better Optimizers Data Driven Optimization General Purpose
Semiring Activation in Neural Networks
Bart M. N. Smets, Peter D. Donker, Jim W. Portegies, Remco Duits
Neural Network Neural Operator Direct Convolution Targeted Activation Penalty

May 28, 2024

Scalable Surrogate Verification of Image-based Neural Network Control Systems using Composition and Unrolling
Feiyang Cai, Chuchu Fan, Stanley Bak
Neural Network Surrogate Model Vision Based Conditional Generative Adversarial Network Safety Guarantee Compositional Ability Reachable Set
SGD method for entropy error function with smoothing l0 regularization for neural networks
Trong-Tuan Nguyen, Van-Dat Thang, Nguyen Van Thin, Phuong T. Nguyen
Neural Network Stochastic Gradient Descent Entropy Model Entropy Function Normal Regularization
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets
Khen Cohen, Noam Levi, Yaron Oz
Neural Network Binary Classification Gaussian Mixture Model High Dimension Covariance Matrix Optimal Classifier Attribute Correlation
Self-Supervised Dual Contouring
Ramana Sundararaman, Roman Klokov, Maks Ovsjanikov
Neural Network Self Supervised Objective Iso Surface Extraction Dual Contouring
$C^2M^3$: Cycle-Consistent Multi-Model Merging
Donato Crisostomi, Marco Fumero, Daniele Baieri, Florian Bernard, Emanuele Rodolà
Neural Network Neuronal Network Cycle Consistency

May 27, 2024

Building a temperature forecasting model for the city with the regression neural network (RNN)
Nguyen Phuc Tran, Duy Thanh Tran, Thi Thuy Nga Duong
Neural Network Recurrent Neural Network Predictive Model Novel Regression Urban Environment \Sigma}{\Delta}$ Low Pas RNN Weather Prediction Model Accurate Predictive Model Urban Temperature
ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers
Quan Liu, Brandon T. Swartz, Ivan Kravchenko, Jason G. Valentine, Yuankai Huo
Neural Network Energy Efficient Neural Network Lightweight Segmentation Metamaterial Neural Network Optical Processing Unit
Probabilistic Verification of Neural Networks using Branch and Bound
David Boetius, Stefan Leue, Tobias Sutter
Neural Network Neural Network Verification Relative Probability Multi Channel Branch Probabilistic Verification
Survival of the Fittest Representation: A Case Study with Modular Addition
Xiaoman Delores Ding, Zifan Carl Guo, Eric J. Michaud, Ziming Liu, Max Tegmark
Neural Network Case Study Meaningful Representation Deep Survival Optimal Representation Modular Addition Competition Dynamic Circle Representation

Neural Network

Papers

Optimizing cnn-Bigru performance: Mish activation and comparative analysis with Relu

Recurrent neural network wave functions for Rydberg atom arrays on kagome lattice

Flexible SE(2) graph neural networks with applications to PDE surrogates

Tropical Expressivity of Neural Networks

Symmetries in Overparametrized Neural Networks: A Mean-Field View

Semantic Landmark Detection & Classification Using Neural Networks For 3D In-Air Sonar

Understanding and Minimising Outlier Features in Neural Network Training

Convex neural network synthesis for robustness in the 1-norm

Few-Shot Testing: Estimating Uncertainty of Memristive Deep Neural Networks Using One Bayesian Test Vector

Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization

Semiring Activation in Neural Networks

Scalable Surrogate Verification of Image-based Neural Network Control Systems using Composition and Unrolling

SGD method for entropy error function with smoothing l0 regularization for neural networks

Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets

Self-Supervised Dual Contouring

$C^2M^3$: Cycle-Consistent Multi-Model Merging

Building a temperature forecasting model for the city with the regression neural network (RNN)

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Probabilistic Verification of Neural Networks using Branch and Bound

Survival of the Fittest Representation: A Case Study with Modular Addition