UNIVERSITETET I OSLO

research

∙ 05/11/2022

Deep Learning and Computer Vision Techniques for Microcirculation Analysis: A Review

The analysis of microcirculation images has the potential to reveal earl...

Maged Abdalla Helmy Mohamed Abdou, et al. ∙

research

∙ 04/30/2020

Named Entity Recognition without Labelled Data: A Weak Supervision Approach

Named Entity Recognition (NER) performance often degrades rapidly when a...

Pierre Lison, et al. ∙

research

∙ 01/11/2022

Adherence Forecasting for Guided Internet-Delivered Cognitive Behavioral Therapy: A Minimally Data-Sensitive Approach

Internet-delivered psychological treatments (IDPT) are seen as an effect...

Ulysse Côté-Allard, et al. ∙

research

∙ 06/18/2020

Likelihood-Free Inference with Deep Gaussian Processes

In recent years, surrogate models have been successfully used in likelih...

Alexander Aushev, et al. ∙

research

∙ 11/02/2021

Likelihood-Free Inference in State-Space Models with Unknown Dynamics

We introduce a method for inferring and predicting latent states in the ...

Alexander Aushev, et al. ∙

research

∙ 04/23/2021

CapillaryNet: An Automated System to Analyze Microcirculation Videos from Handheld Vital Microscopy

Capillaries are the smallest vessels in the body responsible for the del...

Maged Helmy, et al. ∙

research

∙ 01/31/2018

Deep Predictive Models in Interactive Music

Automatic music generation is a compelling task where much recent progre...

Charles P. Martin, et al. ∙

research

∙ 07/13/2017

On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL

In various approaches to learning, notably in domain adaptation, active ...

Marco Loog, et al. ∙

research

∙ 07/07/2016

Mapping Data to Ontologies with Exceptions Using Answer Set Programming

In ontology-based data access, databases are connected to an ontology vi...

Daniel P. Lupp, et al. ∙

research

∙ 06/24/2016

Standard State Space Models of Unawareness (Extended Abstract)

The impossibility theorem of Dekel, Lipman and Rustichini has been thoug...

Peter Fritz, et al. ∙

research

∙ 03/15/2017

3D Vision Guided Robotic Charging Station for Electric and Plug-in Hybrid Vehicles

Electric vehicles (EVs) and plug-in hybrid vehicles (PHEVs) are rapidly ...

Justinas Miseikis, et al. ∙

research

∙ 04/05/2013

Model-based Bayesian Reinforcement Learning for Dialogue Management

Reinforcement learning methods are increasingly used to optimise dialogu...

Pierre Lison, et al. ∙

research

∙ 10/15/2017

NoReC: The Norwegian Review Corpus

This paper presents the Norwegian Review Corpus (NoReC), created for tra...

Erik Velldal, et al. ∙

research

∙ 07/26/2017

Temporal dynamics of semantic relations in word embeddings: an application to predicting armed conflict participants

This paper deals with using word embedding models to trace the temporal ...

Andrey Kutuzov, et al. ∙

research

∙ 04/19/2017

Redefining Context Windows for Word Embedding Models: An Experimental Study

Distributional semantic models learn vector representations of words thr...

Pierre Lison, et al. ∙

research

∙ 08/12/2016

Redefining part-of-speech classes with distributional semantic models

This paper studies how word embeddings trained on the British National C...

Andrey Kutuzov, et al. ∙

research

∙ 04/18/2016

Clustering Comparable Corpora of Russian and Ukrainian Academic Texts: Word Embeddings and Semantic Fingerprints

We present our experience in applying distributional semantics (neural w...

Andrey Kutuzov, et al. ∙

research

∙ 07/01/2016

Massively parallel implementation in Python of a pseudo-spectral DNS code for turbulent flows

Direct Numerical Simulations (DNS) of the Navier Stokes equations is a v...

Mikael Mortensen, et al. ∙

research

∙ 01/06/2018

Robot Localisation and 3D Position Estimation Using a Free-Moving Camera and Cascaded Convolutional Neural Networks

Many works in collaborative robotics and human-robot interaction focuses...

Justinas Miseikis, et al. ∙

research

∙ 01/19/2018

Size vs. Structure in Training Corpora for Word Embedding Models: Araneum Russicum Maximum and Russian National Corpus

In this paper, we present a distributional word embedding model trained ...

Andrey Kutuzov, et al. ∙

research

∙ 03/15/2018

Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing

Robots need to be able to adapt to complex and dynamic environments for ...

Tønnes F. Nygaard, et al. ∙

research

∙ 03/31/2018

The Impact of Quantum Computing on Present Cryptography

The aim of this paper is to elucidate the implications of quantum comput...

Vasileios Mavroeidis, et al. ∙

research

∙ 04/05/2018

The Geometry of SDP-Exactness in Quadratic Optimization

Consider the problem of minimizing a quadratic objective subject to quad...

Diego Cifuentes, et al. ∙

research

∙ 04/06/2018

Multi-Objective Convolutional Neural Networks for Robot Localisation and 3D Position Estimation in 2D Camera Images

The field of collaborative robotics and human-robot interaction often fo...

Justinas Miseikis, et al. ∙

research

∙ 04/15/2018

Are Automatic Methods for Cognate Detection Good Enough for Phylogenetic Reconstruction in Historical Linguistics?

We evaluate the performance of state-of-the-art algorithms for automatic...

Taraka Rama, et al. ∙

research

∙ 04/18/2018

Experiments with Universal CEFR Classification

The Common European Framework of Reference (CEFR) guidelines describe la...

Sowmya Vajjala, et al. ∙

research

∙ 04/25/2018

Fast parallel multidimensional FFT using advanced MPI

We present a new method for performing global redistributions of multidi...

Lisandro Dalcin, et al. ∙

research

∙ 05/08/2018

Exploring Mechanically Self-Reconfiguring Robots for Autonomous Design

Evolutionary robotics has aimed to optimize robot control and morphology...

Tønnes F. Nygaard, et al. ∙

research

∙ 05/09/2018

Real-World Evolution Adapts Robot Morphology and Control to Hardware Limitations

For robots to handle the numerous factors that can affect them in the re...

Tønnes F. Nygaard, et al. ∙

research

∙ 05/09/2018

Three tree priors and five datasets: A study of the effect of tree priors in Indo-European phylogenetics

The age of the root of the Indo-European language family has received mu...

Taraka Rama, et al. ∙

research

∙ 05/28/2018

Syntactic Dependency Representations in Neural Relation Classification

We investigate the use of different syntactic dependency representations...

Farhad Nooralahzadeh, et al. ∙

research

∙ 05/30/2018

Transfer Learning for Unseen Robot Detection and Joint Estimation on a Multi-Objective Convolutional Neural Network

A significant problem of using deep learning techniques is the limited a...

Justinas Miseikis, et al. ∙

research

∙ 06/19/2018

Effective Intersection Theory

Let X ⊂ Y be closed (possibly singular) subschemes of a smooth projectiv...

Corey Harris, et al. ∙

research

∙ 06/22/2018

Assumption Commitment Types for Resource Management in Virtually Timed Ambients

This paper introduces a type system for resource management in the conte...

Einar Broch Johnsen, et al. ∙

research

∙ 06/19/2018

Segre Class Computation and Practical Applications

Let X ⊂ Y be closed (possibly singular) subschemes of a smooth projectiv...

Corey Harris, et al. ∙

research

∙ 09/13/2018

Tübingen-Oslo system: Linear regression works the best at Predicting Current and Future Psychological Health from Childhood Essays in the CLPsych 2018 Shared Task

This paper describes our efforts in predicting current and future psycho...

Çağrı Çöltekin, et al. ∙

research

∙ 09/18/2018

Transfer and Multi-Task Learning for Noun-Noun Compound Interpretation

In this paper, we empirically evaluate the utility of transfer and multi...

Murhaf Fares, et al. ∙

research

∙ 10/01/2018

Counterfactually Fair Prediction Using Multiple Causal Models

In this paper we study the problem of making predictions using multiple ...

Fabio Massimo Zennaro, et al. ∙

research

∙ 11/20/2018

Voronoi Cells of Varieties

Every real algebraic variety determines a Voronoi decomposition of its a...

Diego Cifuentes, et al. ∙

research

∙ 11/20/2018

Privacy Issues and Data Protection in Big Data: A Case Study Analysis under GDPR

Big data has become a great asset for many organizations, promising impr...

Nils Gruschka, et al. ∙

research

∙ 01/10/2019

Gaussian processes with linear operator inequality constraints

This paper presents an approach for constrained Gaussian Process (GP) re...

Christian Agrell, et al. ∙

research

∙ 01/10/2019

Automatic detection of passable roads after floods in remote sensed and social media data

This paper addresses the problem of floods classification and floods aft...

Kashif Ahmad, et al. ∙

research

∙ 01/21/2019

B-spline-like bases for C^2 cubics on the Powell-Sabin 12-split

For spaces of constant, linear, and quadratic splines of maximal smoothn...

Tom Lyche, et al. ∙

research

∙ 02/02/2019

Data Driven Analysis of Tiny Touchscreen Performance with MicroJam

The widespread adoption of mobile devices, such as smartphones and table...

Charles P. Martin, et al. ∙

research

∙ 02/12/2019

Guiding Neuroevolution with Structural Objectives

The structure and performance of neural networks are intimately connecte...

Kai Olav Ellefsen, et al. ∙

research

∙ 02/12/2019

Evolving Robots on Easy Mode: Towards a Variable Complexity Controller for Quadrupeds

The complexity of a legged robot's environment or task can inform how sp...

Tønnes Frostad Nygaard, et al. ∙

research

∙ 02/15/2019

Two-Stage Transfer Learning for Heterogeneous Robot Detection and 3D Joint Position Estimation in a 2D Camera Image using CNN

Collaborative robots are becoming more common on factory floors as well ...

Justinas Miseikis, et al. ∙

research

∙ 03/06/2019

Learning from Higher-Layer Feature Visualizations

Driven by the goal to enable sleep apnea monitoring and machine learning...

Konstantinos Nikolaidis, et al. ∙

research

∙ 03/18/2019

Combining Model and Parameter Uncertainty in Bayesian Neural Networks

Bayesian neural networks (BNNs) have recently regained a significant amo...

Aliaksandr Hubin, et al. ∙

research

∙ 03/23/2019

Volatility and intensity

When studying models and estimators in the setting of high-frequency dat...

Emil A. Stoltenberg, et al. ∙

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