:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Li, Yong, Heng
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2506.04613
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MMET: A Multi-Input and Multi-Scale Transformer for Efficient PDEs Solving
by: Luo, Yichen, et al.
Published: (2025)

Applications of Scientific Machine Learning for the Analysis of Functionally Graded Porous Beams
by: Eshaghi, Mohammad Sadegh, et al.
Published: (2024)

Second Order Bounds for Contextual Bandits with Function Approximation
by: Pacchiano, Aldo
Published: (2024)

SciMON: Scientific Inspiration Machines Optimized for Novelty
by: Wang, Qingyun, et al.
Published: (2023)

Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEs
by: Arndt, Jost, et al.
Published: (2025)

Efficient High-Accuracy PDEs Solver with the Linear Attention Neural Operator
by: Zhong, Ming, et al.
Published: (2025)

Helix 1.0: An Open-Source Framework for Reproducible and Interpretable Machine Learning on Tabular Scientific Data
by: Aguilar-Bejarano, Eduardo, et al.
Published: (2025)

A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models
by: Zhang, Hengyuan, et al.
Published: (2024)

Solving PDEs With Deep Neural Nets under General Boundary Conditions
by: Zhang, Chenggong
Published: (2025)

MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
by: Zhang, Lei, et al.
Published: (2023)

Machine Learning-Based Quantification of Vesicoureteral Reflux with Enhancing Accuracy and Efficiency
by: Alqaraleh, Muhyeeddin, et al.
Published: (2025)

DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
by: Yue, Yang, et al.
Published: (2024)

DeepSeek vs. ChatGPT vs. Claude: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks
by: Jiang, Qile, et al.
Published: (2025)

Modeling chaotic Lorenz ODE System using Scientific Machine Learning
by: Kashyap, Sameera S, et al.
Published: (2024)

A Mass-Conserving-Perceptron for Machine Learning-Based Modeling of Geoscientific Systems
by: Wang, Yuan-Heng, et al.
Published: (2023)

Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries
by: Li, Zhihao, et al.
Published: (2024)

Enabling High Data Throughput Reinforcement Learning on GPUs: A Domain Agnostic Framework for Data-Driven Scientific Research
by: Lan, Tian, et al.
Published: (2024)

Matching Problems to Solutions: An Explainable Way of Solving Machine Learning Problems
by: Saleh, Lokman, et al.
Published: (2024)

A Scientific Machine Learning Approach for Predicting and Forecasting Battery Degradation in Electric Vehicles
by: Murgai, Sharv, et al.
Published: (2024)

Efficient Machine Unlearning via Influence Approximation
by: Liu, Jiawei, et al.
Published: (2025)

Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error
by: Du, Ally Yalei, et al.
Published: (2024)

Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
by: Pourkamali-Anaraki, Farhad, et al.
Published: (2024)

Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator
by: Feng, Xincheng, et al.
Published: (2024)

Causify DataFlow: A Framework For High-performance Machine Learning Stream Computing
by: Saggese, Giacinto Paolo, et al.
Published: (2025)

Towards Learning Foundation Models for Heuristic Functions to Solve Pathfinding Problems
by: Khandelwal, Vedant, et al.
Published: (2024)

High-order Regularization for Machine Learning and Learning-based Control
by: Liu, Xinghua, et al.
Published: (2025)

GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
by: Ye, Haoran, et al.
Published: (2023)

PolySet: Restoring the Statistical Ensemble Nature of Polymers for Machine Learning
by: Ferji, Khalid
Published: (2025)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

Towards Differentially Private Reinforcement Learning with General Function Approximation
by: He, Yi, et al.
Published: (2026)

Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
by: Xu, Qingsong, et al.
Published: (2023)

Guided Diffusion Sampling on Function Spaces with Applications to PDEs
by: Yao, Jiachen, et al.
Published: (2025)

Experiment Planning with Function Approximation
by: Pacchiano, Aldo, et al.
Published: (2024)

Implicit Hypergraph Neural Networks: A Stable Framework for Higher-Order Relational Learning with Provable Guarantees
by: Li, Xiaoyu, et al.
Published: (2025)

Enhancing Neural Function Approximation: The XNet Outperforming KAN
by: Li, Xin, et al.
Published: (2025)

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework
by: Tu, Ruibo, et al.
Published: (2024)

Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
by: Papageorgiou, Yiannis, et al.
Published: (2026)

Subspace-based Approximate Hessian Method for Zeroth-Order Optimization
by: Kim, Dongyoon, et al.
Published: (2025)

Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning
by: Rozada, Sergio, et al.
Published: (2022)

On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation
by: Huang, Jiawei, et al.
Published: (2023)