Spatio-Temporal Graph Neural Networks for Multi-Site PV Power Forecasting

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Low-dimensional perovskite such as layered halide perovskite and perovskite nanocrystals have attracted attention in the past decade. These materials have impressive optoelectronic properties such as high photoluminescence and improved stability relative t ...

We propose a method for unsupervised reconstruction of a temporally-consistent sequence of surfaces from a sequence of time-evolving point clouds. It yields dense and semantically meaningful correspondences between frames. We represent the reconstructed su ...

Machine learning models, meticulously optimized for source data, often fail to predict target data when faced with distribution shifts (DSs). Previous benchmarking studies, though extensive, have mainly focused on simple DSs. Recognizing that DSs often occ ...

This paper studies the problem of learning computable functions in the limit by extending Gold's inductive inference framework to incorporate computational observations and restricted input sources. Complimentary to the traditional Input-Output Observation ...

Lattice light-sheet microscopy provides a crucial observation window into intra- and intercellular physiology of living specimens but at the diffraction-limited resolution or anisotropic super-resolution with structured illumination. Here we present meta-l ...

Infrared light management is crucial to maximize the optical performance of crystalline Si-based single junction and tandem solar cells. For this end, a low refractive index dielectric is typically inserted under the rear metal and an electrical contact is ...

Dynamic hand gesture recognition (HGR) is critical for real-time prosthetics and neural robotics applications, where high-density surface electromyography (HD-sEMG) signals provide valuable insights into muscle activity. However, adapting machine learning ...

The emergence of metal halide perovskite materials has triggered a revolutionary change in optoelectronic devices. Due to their outstanding optoelectronic properties and defect tolerance, metal halide perovskites can be used for a wide range of application ...

From hydropower to wind power, renewable energy is converted to electricity, putting the electric grid at the crossroads of the green energy generation and consumption. The grid must also adapt and scale up to an increased capacity and to the stochastic na ...

Objective. Many psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local fi ...

This thesis focuses on the development of advanced algorithmic techniques, primarily Markov Chain Monte Carlo (MCMC) methods, and message passing algorithms, to tackle high-dimensional optimization and inference problems. The algorithms used have a probabi ...

This dataset contains images (TIFF image data) of brain juvenile rats Wistar Han (P14) scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F5 ...

In this paper, we present a model for the analytical computation of the power flow sensitivity coefficients (SCs) for hybrid AC/DC networks. The SCs are defined as the partial derivates of the nodal voltages with respect to the active and reactive power in ...

The European Green Deal is prescribing a very ambitious rise in the annual production of renewable energy sources, and grid regulation services are increasingly important in the course of a massive integration of intermittent renewable energy sources. Alth ...

In fully supervised learning-based medical image classification, the robustness of a trained model depends on its exposure to various disease classes. Generalized Zero Shot Learning (GZSL) aims to predict both seen and novel unseen classes. While most GZSL ...

Sustainability should be integrated into everything we do, including engineering and student projects. This experiential activity uses the selection of materials for a wind turbine to engage participants in a contextualised negotiation of multiple facets o ...

Thermo-catalytic conversion of CO2 into more valuable compounds, such as methane, is an attractive strategy for energy storage in chemical bonds and creating a carbon-based circular economy. However, designing heterogeneous catalysts remains a challenging, ...

For Graph Neural Networks, oversmoothing denotes the homogenization of vertex embeddings as the number of layers increases. To better understand this phenomenon, we study community detection with a linearized Graph Convolutional Network on the Contextual S ...

Denoising Diffusion Probabilistic Models (DDPMs) exhibit remarkable capabilities in image generation, with studies suggesting that they can generalize by composing latent factors learned from the training data. In this work, we go further and study DDPMs t ...

Perovskite-silicon (Si) tandem solar cells are the most prominent contenders to succeed single-junction Si cells that dominate the market today. Yet, to justify the added cost of inserting a perovskite cell on top of Si, these devices should first exhibit ...

Spatio-Temporal Graph Neural Networks for Multi-Site PV Power Forecasting

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Temporally-Consistent Surface Reconstruction Using Metrically-Consistent Atlases

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Optimal performance of Graph Convolutional Networks on the Contextual Stochastic Block Model

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations

Synergetic substrate and additive engineering for over 30%-efficient perovskite-Si tandem solar cells