publicações selecionadas
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artigo académico
- A Suite of XAI techniques for Understanding Neural Ordinary Differential Equations 2023
- Enhancing Continuous Time Series Mo- delling with a Latent ODE-LSTM Approach 2023
- Enhancing Continuous Time Series Modelling with a Latent ODE-LSTM Approach 2023
- Neural Chronos ODE: Unveiling Temporal Patterns and Forecasting Future and Past Trends in Time Series Data 2023
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artigo de conferência
- A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs 2023
- A Study on Adaptive Penalty Functions in Neural ODEs for Real Systems Modeling 2023
- Prior knowledge meets Neural ODEs: a two-stage training method for improved explainabilitty 2023
- The role of adaptive activation functions in Fractional Physics-Informed Neural Networks 2022
- Improving public parking by using artificial intelligence 2021
- Optimization of traffic lights using Supervised Learning 2021
- The Influence of the Optimization Algorithm in the Solution of the Fractional Laplacian Equation by Neural Networks 2021
- The influence of the optimisation algorithm in the solution of the Fractional Laplacian Equation by neural networks 2021
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capítulo de livro
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documento
- Improving Neural ODEs Explainability: A Two-Stage Training Method for Modeling Constrained Natural Systems 2023
- Not All Roses: The Impact of Neural Networks for Hydropower Plant Management in Agriculture 2023
- Fractional Physics Informed Neural Networks with adaptive activation functions: a numerical study 2022
- Implementation of a Deep Learning model capable of detecting objects from satellite images 2021
- Neural Networks and Fractional Differential Equations 2021
- Parameter Estimation for Constitutive Differential Equations: An Optimization Approach 2021
- Damped Harmonic Oscillator Dataset
- A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs
- Enhancing Continuous Time Series Modelling with a Latent ODE-LSTM Approach
- Neural Chronos ODE: Unveiling Temporal Patterns and Forecasting Future and Past Trends in Time Series Data. ArXiv.
- Synthetic Chemical Reaction Dataset
- World Population Growth Dataset