| Explainable AI (XAI) models applied to the multi-agent environment of financial markets JJ Ohana, S Ohana, E Benhamou, D Saltiel, B Guez Explainable and Transparent AI and Multi-Agent Systems: Third International …, 2021 | 40 | 2021 |
| Deep reinforcement learning (drl) for portfolio allocation E Benhamou, D Saltiel, JJ Ohana, J Atif, R Laraki Machine Learning and Knowledge Discovery in Databases. Applied Data Science …, 2021 | 30 | 2021 |
| Bridging the gap between Markowitz planning and deep reinforcement learning E Benhamou, D Saltiel, S Ungari, A Mukhopadhyay arXiv preprint arXiv:2010.09108, 2020 | 28 | 2020 |
| Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning E Benhamou, D Saltiel, JJ Ohana, J Atif 2020 25th International Conference on Pattern Recognition (ICPR), 10050-10057, 2021 | 27 | 2021 |
| Time your hedge with deep reinforcement learning E Benhamou, D Saltiel, S Ungari, A Mukhopadhyay arXiv preprint arXiv:2009.14136, 2020 | 21 | 2020 |
| Bcma-es: A bayesian approach to cma-es E Benhamou, D Saltiel, S Verel, F Teytaud arXiv preprint arXiv:1904.01401, 2019 | 13 | 2019 |
| Testing Sharpe ratio: luck or skill? E Benhamou, D Saltiel, B Guez, N Paris arXiv preprint arXiv:1905.08042, 2019 | 12 | 2019 |
| Explainable AI (XAI) models applied to planning in financial markets E Benhamou, JJ Ohana, D Saltiel, B Guez | 11 | 2021 |
| Explainable ai models of stock crashes: A machine-learning explanation of the covid march 2020 equity meltdown JJ Ohana, S Ohana, E Benhamou, D Saltiel, B Guez Université Paris-Dauphine Research Paper, 2021 | 8 | 2021 |
| RL 2021c. Knowledge discovery with Deep RL for selecting financial hedges E Benhamou, D Saltiel, S Ungari, JA Abhishek Mukhopadhyay AAAI: KDF, AAAI Press, 0 | 7 | |
| Bcma-es ii: revisiting bayesian cma-es E Benhamou, D Saltiel, B Guez, N Paris arXiv preprint arXiv:1904.01466, 2019 | 6 | 2019 |
| Aamdrl: Augmented asset management with deep reinforcement learning E Benhamou, D Saltiel, S Ungari, A Mukhopadhyay, J Atif arXiv preprint arXiv:2010.08497, 2020 | 5 | 2020 |
| Adaptive learning for financial markets mixing model-based and model-free rl for volatility targeting E Benhamou, D Saltiel, S Tabachnik, SK Wong, F Chareyron arXiv preprint arXiv:2104.10483, 2021 | 4 | 2021 |
| NGO-GM: Natural gradient optimization for graphical models E Benhamou, J Atif, R Laraki, D Saltiel arXiv preprint arXiv:1905.05444, 2019 | 4 | 2019 |
| Feature selection with optimal coordinate ascent (OCA) D Saltiel, E Benhamou arXiv preprint arXiv:1811.12064, 2018 | 3 | 2018 |
| Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? B Lefort, E Benhamou, JJ Ohana, D Saltiel, B Guez, D Challet arXiv preprint arXiv:2401.05447, 2024 | 2 | 2024 |
| FSDA: Tackling Tail-Event Analysis in Imbalanced Time Series Data with Feature Selection and Data Augmentation R Krief, E Benhamou, B Guez, JJ Ohana, D Saltiel, R Laraki, J Atif Available at SSRN 4557797, 2023 | 2 | 2023 |
| Planning in Financial Markets in Presence of Spikes: Using Machine Learning GBDT E Benhamou, JJ Ohana, D Saltiel, B Guez Université Paris-Dauphine Research Paper, 2021 | 2 | 2021 |
| From forecast to decisions in graphical models: A natural gradient optimization approach E Benhamou, D Saltiel, B Guez, J Atif, R Laraki Université Paris-Dauphine Research, 2021 | 2 | 2021 |
| Trade selection with supervised learning and optimal coordinate ascent (OCA) D Saltiel, E Benhamou, R Laraki, J Atif Mining Data for Financial Applications: 5th ECML PKDD Workshop, MIDAS 2020 …, 2021 | 2 | 2021 |
Eric BenhamouUniversité Paris Dauphine, FranceAdresse e-mail validée de dauphine.eu
