Constructing a NFT Price Index and Applications
Schnoering, H., & Inzirillo, H. (2022). Constructing a nft price index and applications. arXiv preprint arXiv:2202.08966.
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Posts by Collection
publications
Deep Fusion of Lead-lag Graphs: Application to Cryptocurrencies
Schnoering, H., & Inzirillo, H. (2022). Deep Fusion of Lead-lag Graphs: Application to Cryptocurrencies. arXiv preprint arXiv:2201.02040.
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An Attention Free Long Short-Term Memory for Time Series Forecasting
Inzirillo, H., & De Villelongue, L. (2022). An attention free long short-term memory for time series forecasting. arXiv preprint arXiv:2209.09548.
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Managing Risk in DeFi Portfolios
Inzirillo, H., & De Quénetain, S. (2022). Managing Risk in DeFi Portfolios. arXiv preprint arXiv:2205.14699.
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An Attention Free Conditional Autoencoder For Anomaly Detection in Cryptocurrencies
Inzirillo, H., & De Villelongue, L. (2023). An Attention Free Conditional Autoencoder For Anomaly Detection in Cryptocurrencies. arXiv preprint arXiv:2304.10614.
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TKAN: Temporal Kolmogorov-Arnold Networks
Genet, R., & Inzirillo, H. (2024). Tkan: Temporal kolmogorov-arnold networks. arXiv preprint arXiv:2405.07344.
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A Temporal Kolmogorov-Arnold Transformer for Time Series Forecasting
Genet, R., & Inzirillo, H. (2024). A Temporal Kolmogorov-Arnold Transformer for Time Series Forecasting. arXiv preprint arXiv:2406.02486.
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SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series
Inzirillo, H., & Genet, R. (2024). SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series. arXiv preprint arXiv:2406.17890.
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Deep State Space Recurrent Neural Networks for Time Series Forecasting
Inzirillo, H. (2024). Deep state space recurrent neural networks for time series forecasting. arXiv preprint arXiv:2407.15236.
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A Gated Residual Kolmogorov-Arnold Networks for Mixtures of Experts
Inzirillo, H., & Genet, R. (2024). A Gated Residual Kolmogorov-Arnold Networks for Mixtures of Experts. arXiv preprint arXiv:2409.15161.
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A Temporal Linear Network for Time Series Forecasting
Genet, R., & Inzirillo, H. (2024). A Temporal Linear Network for Time Series Forecasting. arXiv preprint arXiv:2410.21448.
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CaAdam: Improving Adam optimizer using connection aware methods
Genet, R., & Inzirillo, H. (2024). CaAdam: Improving Adam optimizer using connection aware methods. arXiv preprint arXiv:2410.24216.
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supervision
An Attention-Free LSTM For Time Series Forecasting
Master Thesis, Ludovic de Villelongue, MSc in Quantitative Finance, Université Paris Dauphine - PSL, 2021 - 2022
Volatility Forecasting Using SigGarchNet
Research Project, Nicolas Manelli, MSc in Quantitative Finance, Université Paris Dauphine - PSL, 2022 - 2023
North Leaf Partners
Consulting Project, Kevin Dakpo, MSc in Corporate Finance, EDHEC Business School, 2023 - 2024
talks
teaching
Portfolio Management in Python
Lectures, MSc Quantitative Finance, Université Paris Dauphine - PSL, Department of Quantitative Finance, 2021 - 2023
Intoduction to Python
Lectures, BSc Economics and Financial Engineering, Université Paris Dauphine - PSL, Department of Quantitative Finance, 2021 - 2023
Introduction to econometrics
Lectures, MEng Quantitative Finance, École supérieure d'ingénieurs Léonard-de-Vinci (ESILV), Department of Quantitative Finance, 2021 - 2022
Object Oriented Programming (Python)
Lectures, MSc Quantitative Finance, Université Paris Dauphine - PSL, Department of Quantitative Finance, 2021 - 2023
Build APIs in Python
Lectures, MSc Quantitative Finance, Université Paris Dauphine - PSL, Department of Quantitative Finance, 2021 - 2023
Deep Learning for Time Series
Lectures, MSc Quantitative Finance, Université Paris Dauphine - PSL, Department of Quantitative Finance, 2022 - 2024