Forecasting Application

Forecasting applications aim to predict future values of time series data across diverse domains, from industrial demand to financial markets and transportation systems. Current research emphasizes improving accuracy and scalability of forecasting models, focusing on hierarchical models for complex, sparse data, multimodal networks incorporating diverse data sources (e.g., news, social media), and retrieval-augmented architectures that leverage information across multiple entities. These advancements lead to more accurate and robust predictions, impacting business planning, resource allocation, and risk management across various sectors.

Papers

July 2, 2024

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity
Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash
Time Series Forecasting Sparsity Increase Probabilistic Forecast Hierarchical Time Series Forecasting Forecasting Application

May 3, 2024

Large Language Models for Mobility in Transportation Systems: A Survey on Forecasting Tasks
Zijian Zhang, Yujie Sun, Zepu Wang, Yuqi Nie, Xiaobo Ma, Peng Sun, Ruolin Li
Timely Survey Transportation System Mobility Management Mobility Data Forecasting Task Travel Behavior Human Mobility Forecasting Forecasting Application Traffic State Sequence

October 20, 2022

Multimodal Neural Network For Demand Forecasting
Nitesh Kumar, Kumar Dheenadayalan, Suprabath Reddy, Sumant Kulkarni
Time Series Forecasting Demand Forecasting Open Checkout Free Grocery Multimodal Neural Network Forecasting Application

July 23, 2022

Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification
Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
Pre Trained Model Stock Movement Prediction Bilinear Convolutional Neural Network Forecasting Application

July 21, 2022

MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation
Sitan Yang, Carson Eisenach, Dhruv Madeka
Probabilistic Forecast Retrieval Augmentation Probabilistic Time Series Forecasting Demand Forecasting Multi Horizon Entity Attention Forecasting Application

Forecasting Application

Papers

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity

Large Language Models for Mobility in Transportation Systems: A Survey on Forecasting Tasks

Multimodal Neural Network For Demand Forecasting

Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification

MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation