6 papers
Spatio-temporal Latent Denoising Diffusion Probabilistic Models for Reduced-order Modeling of Parametrized Dynamical Systems
Michiel Nikken, Nicolò Botteghi, Federico Califano +1
Many scientific problems require accurate modeling of complex physical phenomena, such as fluid dynamics or climate modeling. These phenomena often result in high-dimensional and t…
Interconnection and Damping Assignment Passivity-Based Control using Sparse Neural ODEs
Nicolò Botteghi, Owen Brook, Urban Fasel +1
Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) is a nonlinear control technique that assigns a port-Hamiltonian (pH) structure to a controlled system usin…
Shaping Explanations: Semantic Reward Modeling with Encoder-Only Transformers for GRPO
Francesco Pappone, Ruggero Marino Lazzaroni, Federico Califano +2
While Large Language Models (LLMs) excel at generating human-like text, aligning their outputs with complex, qualitative goals like pedagogical soundness remains a significant chal…
From Spectra to Geography: Intelligent Mapping of RRUFF Mineral Data
Francesco Pappone, Federico Califano, Marco Tafani
Accurately determining the geographic origin of mineral samples is pivotal for applications in geology, mineralogy, and material science. Leveraging the comprehensive Raman spectra…
Denoising Diffusion Planner: Learning Complex Paths from Low-Quality Demonstrations
Michiel Nikken, Nicolò Botteghi, Wesley Roozing +1
Denoising Diffusion Probabilistic Models (DDPMs) are powerful generative deep learning models that have been very successful at image generation, and, very recently, in path planni…
Limiting Kinetic Energy through Control Barrier Functions: Analysis and Experimental Validation
Federico Califano, Daniel Logmans, Wesley Roozing
In the context of safety-critical control, we propose and analyse the use of Control Barrier Functions (CBFs) to limit the kinetic energy of torque-controlled robots. The proposed…