Cover Image

SSMT: Few-Shot Traffic Forecasting with Single Source Meta-Transfer

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bhaumik, Kishor Kumar, Kim, Minha, Niloy, Fahim Faisal, Ali, Amin Ahsan, Woo, Simon S.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow Prediction
by: Bhaumik, Kishor Kumar, et al.
Published: (2022)

MIXAD: Memory-Induced Explainable Time Series Anomaly Detection
by: Kim, Minha, et al.
Published: (2024)

Source-Free Online Domain Adaptive Semantic Segmentation of Satellite Images under Image Degradation
by: Niloy, Fahim Faisal, et al.
Published: (2024)

GDFlow: Anomaly Detection with NCDE-based Normalizing Flow for Advanced Driver Assistance System
by: Lee, Kangjun, et al.
Published: (2024)

Towards Source-Free Machine Unlearning
by: Ahmed, Sk Miraj, et al.
Published: (2025)

TUBO: A Tailored ML Framework for Reliable Network Traffic Forecasting
by: Yuan, Zhihang, et al.
Published: (2026)

PIMCST: Physics-Informed Multi-Phase Consensus and Spatio-Temporal Few-Shot Learning for Traffic Flow Forecasting
by: Fofanah, Abdul Joseph, et al.
Published: (2026)

MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
by: Zhang, Baoquan, et al.
Published: (2023)

Meta-Tool: Efficient Few-Shot Tool Adaptation for Small Language Models
by: Kumar, Sachin
Published: (2026)

CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
by: Ahmed, Sk Miraj, et al.
Published: (2024)

Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach
by: Tsoumplekas, Georgios, et al.
Published: (2024)

Human Activity Recognition from Wearable Sensor Data Using Self-Attention
by: Mahmud, Saif, et al.
Published: (2020)

Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
by: Liu, Zhanyu, et al.
Published: (2024)

Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
by: Cho, Seongwoong, et al.
Published: (2024)

Does Prior Data Matter? Exploring Joint Training in the Context of Few-Shot Class-Incremental Learning
by: Kim, Shiwon, et al.
Published: (2025)

Electrocardiogram-Language Model for Few-Shot Question Answering with Meta Learning
by: Tang, Jialu, et al.
Published: (2024)

Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
by: Hamman, Faisal, et al.
Published: (2025)

Cough Classification using Few-Shot Learning
by: Kumar, Yoga Disha Sendhil, et al.
Published: (2025)

Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
by: Ke, Tianjun, et al.
Published: (2023)

Meta-Transfer Derm-Diagnosis: Exploring Few-Shot Learning and Transfer Learning for Skin Disease Classification in Long-Tail Distribution
by: Özdemir, Zeynep, et al.
Published: (2024)

Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecasting
by: Liu, Zhanyu, et al.
Published: (2024)

Meta-Semantics Augmented Few-Shot Relational Learning
by: Wu, Han, et al.
Published: (2025)

A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning
by: Daoudi, Paul, et al.
Published: (2023)

Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data
by: Xiong, Weijiang, et al.
Published: (2025)

Meta-Learning Based Few-Shot Graph-Level Anomaly Detection
by: Li, Liting, et al.
Published: (2025)

HEAL: An Empirical Study on Hallucinations in Embodied Agents Driven by Large Language Models
by: Chakraborty, Trishna, et al.
Published: (2025)

ReAugment: Model Zoo-Guided RL for Few-Shot Time Series Augmentation and Forecasting
by: Yuan, Haochen, et al.
Published: (2024)

FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
by: Ouyang, Pengpeng, et al.
Published: (2025)

LISA: Learning-Integrated Space Partitioning Framework for Traffic Accident Forecasting on Heterogeneous Spatiotemporal Data
by: An, Bang, et al.
Published: (2024)

Unsupervised Meta-Learning via Dynamic Head and Heterogeneous Task Construction for Few-Shot Classification
by: Guan, Yunchuan, et al.
Published: (2024)

Rethinking Test-Time Training: Tilting The Latent Distribution For Few-Shot Source-Free Adaptation
by: Syed, Tahir Qasim, et al.
Published: (2026)

Toward Better Generalization in Few-Shot Learning through the Meta-Component Combination
by: Zeng, Qiuhao
Published: (2025)

Is Meta-Learning Out? Rethinking Unsupervised Few-Shot Classification with Limited Entropy
by: Guan, Yunchuan, et al.
Published: (2025)

MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning
by: Wu, Han, et al.
Published: (2025)

DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentation
by: Karimi, Amin, et al.
Published: (2025)

Discovering EV Charging Site Archetypes Through Few Shot Forecasting: The First U.S.-Wide Study
by: Nikhal, Kshitij, et al.
Published: (2025)

TransferLight: Zero-Shot Traffic Signal Control on any Road-Network
by: Schmidt, Johann, et al.
Published: (2024)

Few-Shot Inspired Generative Zero-Shot Learning
by: Shohag, Md Shakil Ahamed, et al.
Published: (2025)

Few-Shot Cross-Device Transfer for Quantum Noise Modeling on Real Hardware
by: Farib, Sahil Al, et al.
Published: (2026)

Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
by: Luthra, Achleshwar, et al.
Published: (2026)