5 days ago · In this article, we provide the first statistical analysis of their performance by merging the rich theory of controlled differential equations (CDE) and ...

5 days ago · DLOs are infinite-dimensional systems, with their true dynamics governed by partial differential equations. The complexity of learning these equations, combined ...

4 days ago · This theorem extends the approximation capability of neural networks beyond functions to non-linear unbounded operators, which are mappings between infinite- ...

4 days ago · by Wouter Jongeneel. Hi, my name is Wout and I am a researcher broadly interested in the mathematical side of systems & control theory. This page functions as ...

6 days ago · This review focuses primarily on neural operators, built on the success of deep neural networks in the approximation of functions defined on finite dimensional ...

4 days ago · We give two examples of stochastic dynamical systems driven by additive and multiplicative Gaussian noise, and demonstrate the validity of the method by ...

7 days ago · In this paper, we present a model-based reinforcement learning system where the transition model is treated in a Bayesian manner. The approach naturally lends.

6 days ago · The ELLIS PhD & Postdoc Program supports excellent young researchers by connecting them to leading researchers across Europe and offering a variety of ...

3 days ago · This book presents a unified view of modelling, simulation, and control of non- linear dynamical systems using soft computing techniques and fractal theory.

2 days ago · The schedule for 2024 is still being finalized. Recheck this page again closer to the conference start date. Show Detail.