{"total":18,"rows":[{"id":"2111.06581","title":"Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting","created":"2021-11-12","cited_by_count":32,"area":null},{"id":"2310.01327","title":"TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series","created":"2023-10-02","cited_by_count":26,"area":null},{"id":"2210.03137","title":"Deep Inventory Management","created":"2022-10-06","cited_by_count":23,"area":null},{"id":"2104.04610","title":"Deep Time Series Forecasting with Shape and Temporal Criteria","created":"2021-04-09","cited_by_count":10,"area":null},{"id":"2509.19975","title":"From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting","created":"2025-09-24","cited_by_count":10,"area":null},{"id":"2207.10517","title":"MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation","created":"2022-07-21","cited_by_count":9,"area":null},{"id":"2205.14025","title":"Inference and Sampling for Archimax Copulas","created":"2022-05-27","cited_by_count":5,"area":null},{"id":"2310.17168","title":"Learning an Inventory Control Policy with General Inventory Arrival Dynamics","created":"2023-10-26","cited_by_count":5,"area":null},{"id":"2510.02224","title":"Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models","created":"2025-10-02","cited_by_count":4,"area":null},{"id":"2311.17797","title":"Learning to Simulate: Generative Metamodeling via Quantile Regression","created":"2023-11-29","cited_by_count":3,"area":null},{"id":"2309.13303","title":"C$^2$VAE: Gaussian Copula-based VAE Differing Disentangled from Coupled Representations with Contrastive Posterior","created":"2023-09-23","cited_by_count":2,"area":null},{"id":"2410.08378","title":"Deep Generative Quantile Bayes","created":"2024-10-10","cited_by_count":2,"area":null},{"id":"2307.03595","title":"GEANN: Scalable Graph Augmentations for Multi-Horizon Time Series Forecasting","created":"2023-07-07","cited_by_count":1,"area":null},{"id":"2302.01800","title":"Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks","created":"2023-02-03","cited_by_count":0,"area":null},{"id":"2412.00419","title":"AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability","created":"2024-11-30","cited_by_count":0,"area":null},{"id":"2501.14233","title":"A Data-driven Dynamic Temporal Correlation Modeling Framework for Renewable Energy Scenario Generation","created":"2025-01-24","cited_by_count":0,"area":null},{"id":"2605.23632","title":"Gaussian Mixture Copula Processes for Irregular Time Series","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2609.25980","title":"Interweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}