Noticias en español
Creación de agentes basados en gráficos de conocimiento con generación de texto estructurado y modelos open-weights
Abstract: Los gráficos de conocimiento son excelentes para representar y almacenar información heterogénea e interconectada de manera estructurada, capturando de manera eficaz relaciones y atributos complejos en diferentes tipos de datos. La generación de texto estructurado permite crear gráficos de conocimiento al proporcionar resultados perfectamente estructurados, lo que lo convierte en un método ideal para extraer información estructurada. De manera similar, la generación de texto estructurado permite la creación de agentes al definir qué herramientas están permitidas y qué entradas de...
Read MoreImmune selection determines mutational landscape of cancer and predict response to immunotherapies.
Abstract: Natural selection forces govern somatic cell evolution. One of these forces is the immune system that, besides protecting us from viruses and bacteria, recognises our own faulty somatic cells and ultimately shapes the emergence of tumors during a process called immunoediting. However, to what extent genetic variation in cancer undergoes immunoediting, and what are the determinants that predispose somatic cells to become malignant remain poorly understood. By exploiting 10K genomic datasets from 33 tumor types, we have uncovered the extent of natural selection in the cancer genome...
Read MoreTurbulent steady states in the nonlinear Schrodinger equation.
Abstract: The nonlinear Schrodinger (NLS) equation, also known as the Gross-Pitaevskii equation, is one of the most common equations in physics. Its applications go from the propagation of light in nonlinear media to the description of gravity waves and Bose-Einstein condensates. In general, the NLS equation describes the evolution of nonlinear waves. Such waves interact and transfer energy and other invariants along scales in a cascade process. This phenomenon is known as wave turbulence and is described by the (weak) wave turbulence theory (WWT). One of the most significant achievements of...
Read MoreSimplified Kalman filtering for non-linear models.
Abstract: We will discuss the problem of approximate statistical inference in the hidden Markov models where the observation equations are non-linear. We propose a Bayesian approach based on a Gaussian approximation as well as its versions suitable for “large” problems. The proposed approach may be seen as an approximate Kalman filter which is generic in the sense that it can be used for any non-linear relationship between the hidden state and the outcome. We show how the proposed simplified Kalman filter can be used in the context of sport rating where the skills of the...
Read MoreStatistical Matching using KCCA, Super-OM and Autoencoders-CCA
Cédric HEUCHENNE, Université de Liège, Belgium Abstract: The potential to study and improve different aspects of our lives is ever growing thanks to the abundance of data available in today’s modern society. Scientists and researchers often need to analyze data from different sources; the observations, which only share a subset of the variables, cannot always be paired to detect common individuals. This is the case, for example, when the information required to study a certain phenomenon is coming from different sample surveys. Statistical matching is a common practice to...
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