{"total":23,"rows":[{"id":"2307.01717","title":"On the Constrained Time-Series Generation Problem","created":"2023-07-04","cited_by_count":54,"area":null},{"id":"2305.16274","title":"Non-adversarial training of Neural SDEs with signature kernel scores","created":"2023-05-25","cited_by_count":37,"area":null},{"id":"2409.07486","title":"MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model","created":"2024-09-04","cited_by_count":28,"area":null},{"id":"2210.09897","title":"Learning to simulate realistic limit order book markets from data as a World Agent","created":"2022-09-26","cited_by_count":27,"area":null},{"id":"2208.05836","title":"HyperTime: Implicit Neural Representation for Time Series","created":"2022-08-11","cited_by_count":24,"area":null},{"id":"2501.05403","title":"TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts","created":"2025-01-09","cited_by_count":21,"area":null},{"id":"2309.00638","title":"Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network","created":"2023-08-23","cited_by_count":20,"area":null},{"id":"2304.13174","title":"Dynamic Datasets and Market Environments for Financial Reinforcement Learning","created":"2023-04-25","cited_by_count":15,"area":null},{"id":"2306.12806","title":"Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness","created":"2023-06-22","cited_by_count":14,"area":null},{"id":"2308.01915","title":"LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study","created":"2023-07-05","cited_by_count":9,"area":null},{"id":"2411.02947","title":"Time-Causal VAE: Robust Financial Time Series Generator","created":"2024-11-05","cited_by_count":8,"area":null},{"id":"2301.04020","title":"Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence","created":"2022-12-13","cited_by_count":6,"area":null},{"id":"2302.11996","title":"K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs","created":"2023-02-23","cited_by_count":6,"area":null},{"id":"2510.26076","title":"New Money: A Systematic Review of Synthetic Data Generation for Finance","created":"2025-10-30","cited_by_count":5,"area":null},{"id":"2311.11913","title":"Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks","created":"2023-11-20","cited_by_count":4,"area":null},{"id":"2406.10214","title":"Universal randomised signatures for generative time series modelling","created":"2024-06-14","cited_by_count":4,"area":null},{"id":"2502.15757","title":"TLOB: A Novel Transformer Model with Dual Attention for Price Trend Prediction with Limit Order Book Data","created":"2025-02-12","cited_by_count":4,"area":null},{"id":"2301.08688","title":"Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets","created":"2023-01-20","cited_by_count":3,"area":null},{"id":"2208.06244","title":"A Modular Framework for Reinforcement Learning Optimal Execution","created":"2022-08-11","cited_by_count":1,"area":null},{"id":"2309.01784","title":"INTAGS: Interactive Agent-Guided Simulation","created":"2023-09-04","cited_by_count":1,"area":null},{"id":"2503.17909","title":"Financial Wind Tunnel: A Retrieval-Augmented Market Simulator","created":"2025-03-23","cited_by_count":1,"area":null},{"id":"2605.27113","title":"High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2608.13082","title":"LOB-ID: Evaluating Synthetic Market Data by Inception Distances","created":"2026-08-13","cited_by_count":0,"area":null}],"next_cursor":null}