An Ordinal Latent Variable Model of Conflict Intensity

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Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

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 ...

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

The Python library ms3 makes scores (symbolic representations of music) operational for computational approaches by representing their contents as sets of tabular files. Music scores represent relations between sounding events by graphical means. The Free ...

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

Term extraction is an information extraction task at the root of knowledge discovery platforms. Developing term extractors that are able to generalize across very diverse and potentially highly technical domains is challenging, as annotations for domains r ...

At the beginning of the 19th century, the Napoleonic administration introduced a new standardised description system to give an objective account of the form and functions of the city of Venice. The cadastre, deployed on a European scale, was offering for ...

Modern machine learning tools have shown promise in detecting symptoms of neurological disorders. However, current approaches typically train a unique classifier for each subject. This subject-specific training scheme requires long labeled recordings from ...

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 ...

Machine Translation (MT) has made considerable progress in the past two decades, particularly after the introduction of neural network models (NMT). During this time, the research community has mostly focused on modeling and evaluating MT systems at the se ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

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 ...

Pitch-class distributions are of central relevance in music information retrieval, computational musicology and various other fields, such as music perception and cognition. However, despite their structure being closely related to the cognitively and musi ...

We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effect of latent variables, the inferred causal relationships among the observed ...

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...

Displacement data modelling is of great importance for the safety control of concrete dams. The commonly used artificial intelligence method modelled the displacement data at each monitoring point individually, i.e., the data correlations between the monit ...

In this paper we propose a fast novel non-linear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides ...

Automatically extracting information from social media is challenging given that social content is often noisy, ambiguous, and inconsistent. However, as many stories break on social channels first before being picked up by mainstream media, developing meth ...

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

Unsupervised template induction over email data is a central component in applications such as information extraction, document classification, and auto-reply. The benefits of automatically generating such templates are known for structured data, e.g. mach ...

An Ordinal Latent Variable Model of Conflict Intensity

Chattez avec Graph Search

Robust machine learning for neuroscientific inference

Robust Outlier Rejection for 3D Registration with Variational Bayes

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

ms3: A parser for MuseScore files, serving as data factory for annotated music corpora

Modeling Structured Data in Attention-based Models

Unsupervised Term Extraction for Highly Technical Domains

Une approche computationnelle du cadastre napoléonien de Venise

Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection

Contextually Plausible and Diverse 3D Human Motion Prediction

Discourse Phenomena in Machine Translation

Discrete-Choice Mining of Social Processes

Personalizable intervention systems to promote healthy behavior change

The Tonal Diffusion Model

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables

The organisation of science: topics, incentives and funding

Concrete Dam Displacement Prediction Based on an ISODATA-GMM Clustering and Random Coefficient Model

A Novel Short-term Event Extraction Algorithm for Biomedical Signals

Efficient Document Filtering Using Vector Space Topic Expansion and Pattern-Mining: The Case of Event Detection in Microposts

Automated Taxonomy Induction and its Applications

Template Induction over Unstructured Email Corpora