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Found 5 papers, 2 papers with code
A Comprehensive Forecasting Framework based on Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment
Thus, we propose a novel framework "Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment (Multi-Stage HiFoReAd)" to address the challenges of preserving seasonality, ensuring coherence, and improving accuracy.
Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search
Graph neural networks have been successful for machine learning, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem.
Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search
Graph neural networks are useful for learning problems, as well as for combinatorial and graph problems such as the Subgraph Isomorphism Problem and the Traveling Salesman Problem.
Computing Steiner Trees using Graph Neural Networks
Graph neural networks have been successful in many learning problems and real-world applications.
AgentBuddy: A Contextual Bandit based Decision Support System for Customer Support Agents
In this short paper, we present early insights from a Decision Support System for Customer Support Agents (CSAs) serving customers of a leading accounting software.
