Search results for "inference"

Comparing various types of limiting synthesis and prediction of functions

1974

Inferring Learning Strategies from Cultural Frequency Data

2015

Social learning has been identified as one of the fundamentals of culture and therefore the understanding of why and how individuals use social information presents one of the big questions in cultural evolution. To date much of the theoretical work on social learning has been done in isolation of data. Evolutionary models often provide important insight into which social learning strategies are expected to have evolved but cannot tell us which strategies human populations actually use. In this chapter we explore how much information about the underlying learning strategies can be extracted by analysing the temporal occurrence or usage patterns of different cultural variants in a population…

Herramientas estadísticas para resolver contrastes de hipótesis con contenido biológico: su uso en ecología del siglo XXI

2008

Amenudo la formación que han recibido durante la carrera los jóvenes investigadores tiene notables carencias en los aspectos prácticos de diseño experimental, análisis de datos e interpretación de resultados, lo cual limita de manera decisiva el provecho científico futuro de sus actividades. Eso es especialmente cierto en nuestros días, ya que vivimos una revolución importante en el campo de la metodología estadística e incluso en el procedimiento de hacer inferencia (el salto matemático desde las propiedades de nuestra muestra de datos a las de los parámetros desconocidos de la población, nuestro objeto de estudio), que afecta no sólo a los ecólogos sino a muchas otras disciplinas científi…

Providing insights into browntail moth local outbreaks by combining life table data and semi-parametric statistics

2011

1. Life table studies have been an essential tool for the comprehension of insect population dynamics, although their use has been methodologically biased by a primary focus on mortality factors, especially natural enemies. Thus, studies in natural populations may relegate important mortality sources to the ‘unknown’ or ‘residual’ mortality categories. To overcome this limitation, life tables may be complemented by combining them with other approaches. 2. The aim of the present study was to provide insights into browntail moth Euproctis chrysorrhoea L. (Lepidoptera: Lymantriidae) local outbreaks by combining life table data and statistical modelling. First, E. chrysorrhoea population densit…

Application of a Bayesian Spatiotemporal Surveillance Method to NYC Syndromic Data

2014

Incorporating prior knowledge (e.g., the spatial distribution of zip codes and background population effects) into a model using Bayesian methods could potentially improve outbreak detection. We adapted a previously described Bayesian model-based spatiotemporal surveillance technique to daily respiratory syndrome counts in NYC Emergency Department data in 2009, the year of the H1N1 influenza pandemic. Citywide, 56 alarms were produced across 15 zip codes, all during days of elevated respiratory visits. Future work includes evaluating our choice of baseline length, considering other alarm thresholds, and conducting a formal evaluation of the method across five syndromes in NYC.

Emulating the Effects of Radiation-Induced Soft-Errors for the Reliability Assessment of Neural Networks

2021

International audience; Convolutional Neural Networks (CNNs) are currently one of the most widely used predictive models in machine learning. Recent studies have demonstrated that hardware faults induced by radiation fields, including cosmic rays, may significantly impact the CNN inference leading to wrong predictions. Therefore, ensuring the reliability of CNNs is crucial, especially for safety-critical systems. In the literature, several works propose reliability assessments of CNNs mainly based on statistically injected faults. This work presents a software emulator capable of injecting real faults retrieved from radiation tests. Specifically, from the device characterisation of a DRAM m…

Comparing various concepts of function prediction. Part 1.

1974

Prediction: f(m+1) is guessed from given f(0), ..., f(m). Program synthesis: a program computing f is guessed from given f(0), ..., f(m). The hypotheses are required to be correct for all sufficiently large m, or with some positive frequency. These approaches yield a hierarchy of function prediction and program synthesis concepts. The comparison problem of the concepts is solved.

On speeding up synthesis and prediction of functions

1974

Inferring slowly changing dynamic gene-regulatory networks

2014

Dynamic gene-regulatory networks are complex since the interaction patterns between its components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between the random variables. By interpreting the random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…

Optimization of Linearized Belief Propagation for Distributed Detection

2020

In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a network of distributed agents can be approximated by a linear fusion of all the local log-likelihood ratios. The proposed approach clarifies how the BP algorithm works, simplifies the statistical analysis of its behavior, and enables us to develop a performance optimization framework for the BP-based distributed inference systems. Next, we propose a blind learning-adaptation scheme to optimize the system performance when there is no information available a pr…