:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Furlong, Aidan, Salko, Robert, Zhao, Xingang, Wu, Xu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.26541
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prediction of Critical Heat Flux in Rod Bundles Using Tube-Based Hybrid Machine Learning Models in CTF
by: Furlong, Aidan, et al.
Published: (2026)

Physics-Based Hybrid Machine Learning for Critical Heat Flux Prediction with Uncertainty Quantification
by: Furlong, Aidan, et al.
Published: (2025)

Development and Deployment of Hybrid ML Models for Critical Heat Flux Prediction in Annulus Geometries
by: Furlong, Aidan, et al.
Published: (2025)

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal Hydraulics Code
by: Furlong, Aidan, et al.
Published: (2025)

Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural Networks
by: Furlong, Aidan, et al.
Published: (2025)

Predicting Critical Heat Flux with Uncertainty Quantification and Domain Generalization Using Conditional Variational Autoencoders and Deep Neural Networks
by: Alsafadi, Farah, et al.
Published: (2024)

Data-Driven Prediction and Uncertainty Quantification of PWR Crud-Induced Power Shift Using Convolutional Neural Networks
by: Furlong, Aidan, et al.
Published: (2024)

A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings
by: Agarwal, Sidharth, et al.
Published: (2025)

Knowledge from Large-Scale Protein Contact Prediction Models Can Be Transferred to the Data-Scarce RNA Contact Prediction Task
by: Jian, Yiren, et al.
Published: (2023)

Learning Shortest Paths When Data is Scarce
by: Matsypura, Dmytro, et al.
Published: (2026)

Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data
by: Li, Yujie, et al.
Published: (2025)

Pre-trained Encoders for Global Child Development: Transfer Learning Enables Deployment in Data-Scarce Settings
by: Fahim, Md Muhtasim Munif, et al.
Published: (2026)

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification
by: Tang, Weitao, et al.
Published: (2025)

Robust Molecular Property Prediction via Densifying Scarce Labeled Data
by: Kim, Jina, et al.
Published: (2025)

Causality Enhanced Origin-Destination Flow Prediction in Data-Scarce Cities
by: Feng, Tao, et al.
Published: (2025)

An Algorithm for Learning Smaller Representations of Models With Scarce Data
by: de Wynter, Adrian
Published: (2020)

Source -Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels
by: Elia, Shlomo Salo, et al.
Published: (2024)

Personalized Treatment Outcome Prediction from Scarce Data via Dual-Channel Knowledge Distillation and Adaptive Fusion
by: Chen, Wenjie, et al.
Published: (2025)

Stroke Prediction using Clinical and Social Features in Machine Learning
by: Chadha, Aidan
Published: (2024)

Rethinking Remaining Useful Life Prediction with Scarce Time Series Data: Regression under Indirect Supervision
by: Cheng, Jiaxiang, et al.
Published: (2025)

Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data
by: Mostafiz, Mir Imtiaz, et al.
Published: (2024)

Cross-Learning from Scarce Data via Multi-Task Constrained Optimization
by: Agorio, Leopoldo, et al.
Published: (2025)

When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
by: Wu, Boqian, et al.
Published: (2026)

Tackling Incomplete Data in Air Quality Prediction: A Bayesian Deep Learning Framework for Uncertainty Quantification
by: Pian, Yuzhuang, et al.
Published: (2025)

SmallML: Bayesian Transfer Learning for Small-Data Predictive Analytics
by: Leontev, Semen
Published: (2025)

ScarceGAN: Discriminative Classification Framework for Rare Class Identification for Longitudinal Data with Weak Prior
by: Chakrabarty, Surajit, et al.
Published: (2025)

PMLBmini: A Tabular Classification Benchmark Suite for Data-Scarce Applications
by: Knauer, Ricardo, et al.
Published: (2024)

Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data
by: Wang, Zhenzhong, et al.
Published: (2024)

Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics
by: Banerjee, S., et al.
Published: (2020)

A Novel Review of Stability Techniques for Improved Privacy-Preserving Machine Learning
by: DuPlessie, Coleman, et al.
Published: (2024)

Hybrid Deep Convolutional Neural Networks Combined with Autoencoders And Augmented Data To Predict The Look-Up Table 2006
by: Djeddou, Messaoud, et al.
Published: (2024)

APEX: Amplitude Anchors and Phase Priors for Target-Scarce Higher-Frequency Wave Prediction
by: Sun, Yifan, et al.
Published: (2026)

Learning Continuous Network Emerging Dynamics from Scarce Observations via Data-Adaptive Stochastic Processes
by: Cui, Jiaxu, et al.
Published: (2023)

A Comparative Analysis of LLM Adaptation: SFT, LoRA, and ICL in Data-Scarce Scenarios
by: Bohnet, Bernd, et al.
Published: (2025)

Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy
by: Wu, Jiahui, et al.
Published: (2024)

A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices
by: Gong, Chen, et al.
Published: (2025)

Knowledge-Data Dually Driven Paradigm for Accurate Landslide Susceptibility Prediction under Data-Scarce Conditions Using Geomorphic Priors and Tabular Foundation Model
by: Yang, Yuting, et al.
Published: (2026)

MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
by: Rex, Atticus, et al.
Published: (2026)

ParaGate: Parasitic-Driven Domain Adaptation Transfer Learning for Netlist Performance Prediction
by: Sun, Bin, et al.
Published: (2025)

Maximizing Information in Domain-Invariant Representation Improves Transfer Learning
by: Li, Adrian Shuai, et al.
Published: (2023)