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Symbiosis between quantum physics and machine learning: Applications in data science, many-body physics and quantum computation
(Universidad Nacional de ColombiaBogotá - Ciencias - Doctorado en Ciencias - FísicaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá, 2022-12-01)
This thesis explores the intersections between quantum computing, quantum physics and machine learning. In the three fields, estimating probability distributions plays a central role. In the case of quantum computing and ...
Benzo[c]quinolizin-3-ones theoretical investigation: SAR analysis and application to nontested compounds
(Amer Chemical SocWashingtonEUA, 2004)
SPICE Simulation of RRAM-Based Cross-Point Arrays Using the Dynamic Memdiode Model
(Frontiers Media, 2021-09)
We thoroughly investigate the performance of the Dynamic Memdiode Model (DMM) when used for simulating the synaptic weights in large RRAM-based cross-point arrays (CPA) intended for neuromorphic computing. The DMM is in ...
NMR calculations with quantum methods: development of new tools for structural elucidation and beyond
(American Chemical Society, 2020-08)
ConspectusStructural elucidation is an important and challenging stage in the discovery of new organic molecules. Single-crystal X-ray analysis provides the most unquestionable results, though in practice the availability ...
Quantum measurement learning for medical image classification
(Universidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería de Sistemas y ComputaciónDepartamento de Ingeniería de Sistemas e IndustrialFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá, 2022-03)
Deep neural networks are the state-of-the-art for medical image classification. However, these models require large data sets to be trained, and they lack some interpretability on their predictions. In recent years, there ...
Aplicación del aprendizaje automático a sistemas cuánticos de pocas partículas confinadas e interactuantes
(2022)
El aprendizaje automático puede ser utilizado para determinar modelos óptimos a partir de conjuntos de datos de lo más variado, en problemas de clasificación, reconocimiento de patrones, etc. En el caso de la Mecánica ...