Discovering Routines from Large-Scale Human Locations using Probabilistic Topic Models

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Accurately estimating model performance poses a significant challenge, particularly in scenarios where the source and target domains follow different data distributions. Most existing performance prediction methods heavily rely on the source data in their ...

Reflective writing is known as a useful method in learning sciences to improve the metacognitive skills of students. However, students struggle to structure their reflections properly, limiting the possible learning gains. Previous works in educational tec ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of '' who did what to whom '' micro-records that enable datadriven approaches to monitoring confl ...

Curiosity refers to the intrinsic desire of humans and animals to explore the unknown, even when there is no apparent reason to do so. Thus far, no single, widely accepted definition or framework for curiosity has emerged, but there is growing consensus th ...

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

Topic models are useful tools for analyzing and interpreting the main underlying themes of large corpora of text. Most topic models rely on word co-occurrence for computing a topic, i.e., a weighted set of words that together represent a high-level semanti ...

This thesis describes advances in the use of novel configurations of non-invasive brain stimulation over the visual system allowing to modulate of modifying electro-physiological activity, interregional interactions and by it, visual behavior such as motio ...

Social isolation negatively affects health, induces detrimental behaviors, and shortens lifespan in social species. Little is known about the mechanisms underpinning these effects because model species are typically short-lived and non-social. Using coloni ...

The nucleus accumbens (NAc) is a brain hub regulating motivated behaviors, including social competitiveness. Mitochondrial function in the NAc links anxiety with social competitiveness, and the mitochondrial fusion protein mitofusin 2 (Mfn2) in NAc neurons ...

We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses. In this context, a popular approach consists of using a Conditional Variational Autoencoder (CVAE). How ...

In the context of learning from demonstration (LfD), trajectory policy representations such as probabilistic movement primitives (ProMPs) allow for rich modeling of demonstrated skills. To reproduce a learned skill with a real robot, a feedback controller ...

This paper studies the routing and charging behaviors of electric vehicles in a competitive ride-hailing market. When the vehicles are idle, they can choose whether to continue cruising to search for passengers, or move a charging station to recharge. The ...

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

The use of smartphone sensing for public health studies is appealing to understand routines. We present an approach to learn nightlife routines in a smartphone sensing dataset volunteered by 184 young people (1586 weekend nights with location data captured ...

Adopting healthy behaviors can prevent the onset of many adverse health conditions. However, behavior changes are difficult to make, and often, people who like to improve their behaviors do not know how to do that. Personalizable intervention systems could ...

A survey of 1206 participants investigated determinants of positive environmental behaviors (PEBs) in Switzerland. Based on a principle component analysis on data for 23 different PEBs, three behavior types were distinguished: (i) public sphere PEBs with p ...

Although often regarded a childhood toy, the design of paper airplanes is subtly complex. The design space and mapping from geometry to distance flown is highly nonlinear and probabilistic where a single airplane design exhibits a multitude of trajectory f ...

Discovering Routines from Large-Scale Human Locations using Probabilistic Topic Models

Chattez avec Graph Search

Source-Free Domain-Invariant Performance Prediction

Metacognition meets AI: Empowering reflective writing with large language models

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

An Ordinal Latent Variable Model of Conflict Intensity

Curiosity-driven exploration: foundations in neuroscience and computational modeling

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Self-Supervised Neural Topic Modeling

Orchestration of oscillatory activity to improve visual motion discrimination

Social isolation shortens lifespan through oxidative stress in ants

Mitofusin-2 in nucleus accumbens D2-MSNs regulates social dominance and neuronal function

Contextually Plausible and Diverse 3D Human Motion Prediction

Probabilistic Adaptive Control for Robust Behavior Imitation

Routing and charging game in ride-hailing service with electric vehicles

Robust Outlier Rejection for 3D Registration with Variational Bayes

Learning Urban Nightlife Routines from Mobile Data

Personalizable intervention systems to promote healthy behavior change

Determinants of Different Types of Positive Environmental Behaviors: An Analysis of Public and Private Sphere Actions

Robotic automation and unsupervised cluster assisted modeling for solving the forward and reverse design problem of paper airplanes