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View article: MBRNet: a multi-view feature fusion Mamba network for LiDAR-based place recognition
MBRNet: a multi-view feature fusion Mamba network for LiDAR-based place recognition Open
LiDAR-based place recognition(LPR) is a crucial technology for autonomous driving to achieve reliable localisation in GPS-denied environments. LPR achieves place recognition and localisation by querying for nearest neighbours in the databa…
View article: MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions
MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions Open
Mathematical formulas are the language of communication between humans and nature. Discovering latent formulas from observed data is an important challenge in artificial intelligence, commonly known as symbolic regression(SR). The current …
View article: Integrating Synaptic Synergy Prompt and Optimized Prototype Classifiers to Enhance Few-Shot Class-Incremental Learning
Integrating Synaptic Synergy Prompt and Optimized Prototype Classifiers to Enhance Few-Shot Class-Incremental Learning Open
View article: DN-CL: Deep Symbolic Regression against Noise via Contrastive Learning
DN-CL: Deep Symbolic Regression against Noise via Contrastive Learning Open
Noise ubiquitously exists in signals due to numerous factors including physical, electronic, and environmental effects. Traditional methods of symbolic regression, such as genetic programming or deep learning models, aim to find the most f…
View article: Generative Pre-Trained Transformer for Symbolic Regression Base In-Context Reinforcement Learning
Generative Pre-Trained Transformer for Symbolic Regression Base In-Context Reinforcement Learning Open
The mathematical formula is the human language to describe nature and is the essence of scientific research. Finding mathematical formulas from observational data is a major demand of scientific research and a major challenge of artificial…
View article: MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task
MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task Open
Mathematical formulas are the crystallization of human wisdom in exploring the laws of nature for thousands of years. Describing the complex laws of nature with a concise mathematical formula is a constant pursuit of scientists and a great…
View article: PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression Open
Symbolic regression aims to derive interpretable symbolic expressions from data in order to better understand and interpret data. %which plays an important role in knowledge discovery and interpretable machine learning. In this study, a sy…
View article: Discovering Mathematical Formulas from Data via GPT-guided Monte Carlo Tree Search
Discovering Mathematical Formulas from Data via GPT-guided Monte Carlo Tree Search Open
Finding a concise and interpretable mathematical formula that accurately describes the relationship between each variable and the predicted value in the data is a crucial task in scientific research, as well as a significant challenge in a…
View article: A Novel Paradigm for Neural Computation: X-Net with Learnable Neurons and Adaptable Structure
A Novel Paradigm for Neural Computation: X-Net with Learnable Neurons and Adaptable Structure Open
Multilayer perception (MLP) has permeated various disciplinary domains, ranging from bioinformatics to financial analytics, where their application has become an indispensable facet of contemporary scientific research endeavors. However, M…
View article: Incorporating Higher-Knowledge into Deep Symbolic Regression Under Generative Neural Network Framework
Incorporating Higher-Knowledge into Deep Symbolic Regression Under Generative Neural Network Framework Open
View article: Camo: Capturing the Modularity by End-to-End Models for Symbolic Regression
Camo: Capturing the Modularity by End-to-End Models for Symbolic Regression Open
View article: MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions
MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions Open
Mathematical formulas serve as the means of communication between humans and nature, encapsulating the operational laws governing natural phenomena. The concise formulation of these laws is a crucial objective in scientific research and an…
View article: Theoretical analysis of induction heating in high-temperature epitaxial growth system
Theoretical analysis of induction heating in high-temperature epitaxial growth system Open
The temperature uniformity and heating efficiency in a high-temperature epitaxial growth system were investigated by modeling and simulating. The finite element method (FEM) was used to calculate the distribution of magnetic field and temp…
View article: A Solar Cell Powered Adaptive Charging Circuit for CMOS Integrated Micro Fuel Cells
A Solar Cell Powered Adaptive Charging Circuit for CMOS Integrated Micro Fuel Cells Open
This paper presents an autonomous interface circuit which uses solar cells to automatically recharge chip integrated micro fuel cell accumulator arrays. These accumulators comprise a fuel cell for powering systems and a hydrolysis cell for…
View article: Effect of As pressure-modulated InAlAs superlattice on the morphology of InAs nanostructures grown on InAs/InAlAs/InP
Effect of As pressure-modulated InAlAs superlattice on the morphology of InAs nanostructures grown on InAs/InAlAs/InP Open
InAs/InAlAs/InP(001) nanostructure materials are grown using solid-source molecular beam epitaxy equipment. Effect of As pressure-modulated InAlAs superlattice on the morphology of InAs nanostructure is investigated. The results show that …