Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.
Simultaneously, a critical pain point arises as several computer vision applications are deploye ...
In the domain of perovskite solar cells (PSCs), the imperative to reconcile impressive photovoltaic performance with lead-related issue and environmental stability has driven innovative solutions. This study pioneers an approach that not only rectifies lea ...
During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...
In this work, we provide a mechanistic understanding of the degradation of perovskite solar cells in operation by focusing on methylammonium lead triiodide (CH3NH3PbI3 or MAPbI3) and tracking the evolution of electronic defects via photo-induced current tr ...
The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...
Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...
In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...
Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...
Snow plays a crucial role in processes regulating ecosystems, the climate, and human development. Mountain snowpack in particular has great relevance for downstream communities. Knowledge about the distribution and properties of the snowpack thus help in p ...
