Semi-Markov model for simulating MOOC students

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In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

This thesis is devoted to the construction, analysis, and implementation of two types of hierarchical Markov Chain Monte Carlo (MCMC) methods for the solution of large-scale Bayesian Inverse Problems (BIP). The first hierarchical method we present is base ...

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...

This paper proposes a studied case to assess the EMF (electromagnetic field) exposure distribution for a specific deployment scenario. This developed novel approach based on a Monte-Carlo (MC) approach took into account the non-uniform user distribution an ...

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

Over the past few years, there has been an increase in the use of chatbots for educational purposes. Nevertheless, the chatbot technologies and architectures that are often applied to educational contexts are not necessarily designed for such contexts. Whi ...

The presence of conversational agents (or chatbots) in educational contexts has been steadily increasing over the past few years. Recent surveys have shown widespread interest in the use of chatbots in education, both for research and practice. Although th ...

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counterintuitive prope ...

In this work, we present, analyze, and implement a class of multilevel Markov chain Monte Carlo(ML-MCMC) algorithms based on independent Metropolis--Hastings proposals for Bayesian inverse problems. In this context, the likelihood function involves solving ...

Neural functions operate in tightly controlled conditions that are mediated by multiple electrical and chemical phenomena. Brain disorders such as Parkinson's Disease and Alzheimer's Disease perturb these conditions and cause a loss of neurons, which impai ...

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

The recent rise in both popularity and performance of large language models has garnered considerable interest regarding their applicability to education. Technologies like ChatGPT, which can engage in human-like dialog, have already disrupted educational ...

We present the measurements of the small-scale clustering for the emission-line galaxy (ELG) sample from the extended Baryon Oscillation Spectroscopic Surv e y (eBOSS) in the Sloan Digital Sk y Surv e y IV (SDSS-IV). We use conditional abundance matching m ...

As more educational activities are conducted online, the need for interactive applications (apps) that can effectively support educators in their practice is increasing. These apps are often created by web developers or by researchers, educators, and even ...

Microchannel plates based on amorphous silicon have the inherent capability to overcome the existing spatial and temporal resolution limitations of single photon detectors. A Monte Carlo model-based study is presented here that serves to exploit their full ...

Deep learning models for learning analytics have become increasingly popular over the last few years; however, these approaches are still not widely adopted in real-world settings, likely due to a lack of trust and transparency. In this paper, we tackle th ...

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

Semi-Markov model for simulating MOOC students

Chat with Graph Search

Gibbs sampling the posterior of neural networks

On distributional autoregression and iterated transportation

HIERARCHICAL MARKOV CHAIN MONTE CARLO METHODS FOR BAYESIAN INVERSE PROBLEMS

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Sampling-Based AQP in Modern Analytical Engines

Revisiting adversarial training for the worst-performing class

Monte-Carlo Method for EMF Exposure Distribution Assessment in 5G Base Station

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

A Blueprint for Integrating Task-Oriented Conversational Agents in Education

A Conceptual Framework for Integrating Conversational Agents in Digital Education

Space Oddity? A Statistical Formulation of Conjunction Assessment

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

A neural probe to sample brain fluid in nanoliter volumes for quantitative molecular studies

Integrated Model for Comprehensive Digital Education Platforms

Prompting Large Language Models to Power Educational Chatbots

Abundance matching analysis of the emission-line galaxy sample in the extended Baryon Oscillation Spectroscopic Survey

Supporting Developers in Creating Web Apps for Education via an App Development Framework

Single photon detection with amorphous silicon-based microchannel plates: A Monte Carlo model

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

Stochastic adaptive resampling for the estimation of discrete choice models