Imagen de Portada

Knowledge-guided Machine Learning: Current Trends and Future Prospects

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Karpatne, Anuj, Jia, Xiaowei, Kumar, Vipin
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence Computational Engineering, Finance, and Science
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
por: Zhao, Lifan, et al.
Publicado: (2023)

Bitcoin Price Prediction using Machine Learning and Combinatorial Fusion Analysis
por: Wu, Yuanhong, et al.
Publicado: (2026)

Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials
por: Nourollah, Amir Masoud, et al.
Publicado: (2026)

Instructor-inspired Machine Learning for Robust Molecular Property Prediction
por: Wu, Fang, et al.
Publicado: (2023)

FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
por: Liu, Jiashuo, et al.
Publicado: (2026)

Recent Trends in Artificial Intelligence-inspired Electronic Thermal Management
por: Chharia, Aviral, et al.
Publicado: (2021)

LLM-guided Chemical Process Optimization with a Multi-Agent Approach
por: Zeng, Tong, et al.
Publicado: (2025)

A Graph Machine Learning Approach for Detecting Topological Patterns in Transactional Graphs
por: Zola, Francesco, et al.
Publicado: (2025)

Courant: a State-Adaptive Perceiver-Based Neural Surrogate with Local Support and Interpretable Field Decomposition
por: Kumar, Anuj, et al.
Publicado: (2026)

AgenticSciML: Collaborative Multi-Agent Systems for Emergent Discovery in Scientific Machine Learning
por: Jiang, Qile, et al.
Publicado: (2025)

FETS Benchmark: Foundation Models Outperform Dataset-specific Machine Learning in Energy Time Series Forecasting
por: Obermeier, Marco, et al.
Publicado: (2026)

A Survey of AI-Powered Mini-Grid Solutions for a Sustainable Future in Rural Communities
por: Pirie, Craig, et al.
Publicado: (2024)

Sparse Latent Factor Forecaster (SLFF) with Iterative Inference for Transparent Multi-Horizon Commodity Futures Prediction
por: Gupta, Abhijit
Publicado: (2025)

EverAdapt: Continuous Adaptation for Dynamic Machine Fault Diagnosis Environments
por: Edward, et al.
Publicado: (2024)

Interactive and Intelligent Root Cause Analysis in Manufacturing with Causal Bayesian Networks and Knowledge Graphs
por: Wehner, Christoph, et al.
Publicado: (2024)

MolProphecy: Bridging Medicinal Chemists' Knowledge and Molecular Pre-Trained Models via a Multi-Modal Framework
por: Zhao, Jianping, et al.
Publicado: (2025)

DK-Root: A Joint Data-and-Knowledge-Driven Framework for Root Cause Analysis of QoE Degradations in Mobile Networks
por: Li, Qizhe, et al.
Publicado: (2025)

Deep Learning Models Meet Financial Data Modalities
por: Khubiev, Kasymkhan, et al.
Publicado: (2025)

Probabilistic Retrofitting of Learned Simulators
por: Diaconu, Cristiana, et al.
Publicado: (2026)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
por: Wang, Shengkun, et al.
Publicado: (2024)

Sparse Computations in Deep Learning Inference
por: Tasou, Ioanna, et al.
Publicado: (2025)

Tabular Learning: Encoding for Entity and Context Embeddings
por: Reusser, Fredy
Publicado: (2024)

Era Splitting: Invariant Learning for Decision Trees
por: DeLise, Timothy
Publicado: (2023)

End-to-End Probabilistic Framework for Learning with Hard Constraints
por: Utkarsh, Utkarsh, et al.
Publicado: (2025)

LASER: Learning Active Sensing for Continuum Field Reconstruction
por: Deng, Huayu, et al.
Publicado: (2026)

Exploring Various Sequential Learning Methods for Deformation History Modeling
por: Yatkin, Muhammed Adil, et al.
Publicado: (2025)

Learning Individual Dynamics from Sparse Cross-Sectional Snapshots
por: Lagemann, Christian, et al.
Publicado: (2026)

Learning-Based Finite Element Methods Modeling for Complex Mechanical Systems
por: Shi, Jiasheng, et al.
Publicado: (2024)

Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization
por: Li, Tao, et al.
Publicado: (2026)

Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
por: Yu, Youn-Yeol, et al.
Publicado: (2023)

Optimize Flip Angle Schedules In MR Fingerprinting Using Reinforcement Learning
por: Zhong, Shenjun, et al.
Publicado: (2025)

CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting
por: Wan, Shu, et al.
Publicado: (2025)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
por: Wang, Mengyu, et al.
Publicado: (2024)

CatMemo at the FinLLM Challenge Task: Fine-Tuning Large Language Models using Data Fusion in Financial Applications
por: Cao, Yupeng, et al.
Publicado: (2024)

Hidformer: Transformer-Style Neural Network in Stock Price Forecasting
por: Szydłowski, Kamil Ł., et al.
Publicado: (2024)

Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns
por: Zhu, Haoren, et al.
Publicado: (2024)

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
por: Jimenez-Roa, Lisandro A., et al.
Publicado: (2024)

Reinforced Symbolic Learning with Logical Constraints for Predicting Turbine Blade Fatigue Life
por: Li, Pei, et al.
Publicado: (2024)

DeepFEA: Deep Learning for Prediction of Transient Finite Element Analysis Solutions
por: Triantafyllou, Georgios, et al.
Publicado: (2024)

R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
por: Li, Yuante, et al.
Publicado: (2025)