Search Results for author: Christian Hansen

Found 26 papers, 13 papers with code

Predicting 4D Liver MRI for MR-guided Interventions

no code implementations25 Feb 2022 Gino Gulamhussene, Anneke Meyer, Marko Rak, Oleksii Bashkanov, Jazan Omari, Maciej Pech, Christian Hansen

Our method can be used in two ways: First, it can reconstruct near real-time 4D MRI with high quality and high resolution (209x128x128 matrix size with isotropic 1. 8mm voxel size and 0. 6s/volume) given a dynamic interventional 2D navigator slice for guidance during an intervention.

MRI Reconstruction

Sequential Modelling with Applications to Music Recommendation, Fact-Checking, and Speed Reading

no code implementations11 Sep 2021 Christian Hansen

Sequential modelling entails making sense of sequential data, which naturally occurs in a wide array of domains.

Fact Checking

2.5D Thermometry Maps for MRI-guided Tumor Ablation

1 code implementation12 Aug 2021 Julian Alpers, Daniel L. Reimert, Maximilian Rötzer, Thomas Gerlach, Marcel Gutberlet, Frank Wacker, Bennet Hensen, Christian Hansen

For reconstruction, we use a weighted interpolation on a cylindric coordinate representation to calculate the heat value of voxels in a region of interest.

Automatic Fake News Detection: Are Models Learning to Reason?

1 code implementation ACL 2021 Casper Hansen, Christian Hansen, Lucas Chaves Lima

Most fact checking models for automatic fake news detection are based on reasoning: given a claim with associated evidence, the models aim to estimate the claim veracity based on the supporting or refuting content within the evidence.

Fact Checking Fake News Detection

Uncertainty-Aware Temporal Self-Learning (UATS): Semi-Supervised Learning for Segmentation of Prostate Zones and Beyond

no code implementations8 Apr 2021 Anneke Meyer, Suhita Ghosh, Daniel Schindele, Martin Schostak, Sebastian Stober, Christian Hansen, Marko Rak

Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and peripheral zone (PZ).

Hippocampus Lesion Segmentation +3

Unsupervised Multi-Index Semantic Hashing

1 code implementation26 Mar 2021 Christian Hansen, Casper Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma

In this work, we propose Multi-Index Semantic Hashing (MISH), an unsupervised hashing model that learns hash codes that are both effective and highly efficient by being optimized for multi-index hashing.

Information Retrieval

Projected Hamming Dissimilarity for Bit-Level Importance Coding in Collaborative Filtering

1 code implementation26 Mar 2021 Christian Hansen, Casper Hansen, Jakob Grue Simonsen, Christina Lioma

While this is highly efficient, each bit dimension is equally weighted, which means that potentially discriminative information of the data is lost.

Collaborative Filtering

Learning Multi-Modal Volumetric Prostate Registration with Weak Inter-Subject Spatial Correspondence

no code implementations9 Feb 2021 Oleksii Bashkanov, Anneke Meyer, Daniel Schindele, Martin Schostak, Klaus Tönnies, Christian Hansen, Marko Rak

We show that the combination of mDSC and SDM similarity measures results in a more accurate and natural transformation pattern together with a stronger gradient coverage.

Image Registration

Multi-Head Self-Attention with Role-Guided Masks

1 code implementation22 Dec 2020 Dongsheng Wang, Casper Hansen, Lucas Chaves Lima, Christian Hansen, Maria Maistro, Jakob Grue Simonsen, Christina Lioma

The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms.

Machine Translation Text Classification +1

Denmark's Participation in the Search Engine TREC COVID-19 Challenge: Lessons Learned about Searching for Precise Biomedical Scientific Information on COVID-19

no code implementations25 Nov 2020 Lucas Chaves Lima, Casper Hansen, Christian Hansen, Dongsheng Wang, Maria Maistro, Birger Larsen, Jakob Grue Simonsen, Christina Lioma

This report describes the participation of two Danish universities, University of Copenhagen and Aalborg University, in the international search engine competition on COVID-19 (the 2020 TREC-COVID Challenge) organised by the U. S. National Institute of Standards and Technology (NIST) and its Text Retrieval Conference (TREC) division.

Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI

1 code implementation23 Sep 2020 Anneke Meyer, Grzegorz Chlebus, Marko Rak, Daniel Schindele, Martin Schostak, Bram van Ginneken, Andrea Schenk, Hans Meine, Horst K. Hahn, Andreas Schreiber, Christian Hansen

Background and Objective: Accurate and reliable segmentation of the prostate gland in MR images can support the clinical assessment of prostate cancer, as well as the planning and monitoring of focal and loco-regional therapeutic interventions.

Hyperparameter Optimization

Unsupervised Semantic Hashing with Pairwise Reconstruction

1 code implementation1 Jul 2020 Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma

Inspired by this, we present Semantic Hashing with Pairwise Reconstruction (PairRec), which is a discrete variational autoencoder based hashing model.

Semantic Similarity Semantic Textual Similarity

Factuality Checking in News Headlines with Eye Tracking

1 code implementation17 Jun 2020 Christian Hansen, Casper Hansen, Jakob Grue Simonsen, Birger Larsen, Stephen Alstrup, Christina Lioma

We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines.

Content-aware Neural Hashing for Cold-start Recommendation

1 code implementation31 May 2020 Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma

NeuHash-CF is modelled as an autoencoder architecture, consisting of two joint hashing components for generating user and item hash codes.

Collaborative Filtering Recommendation Systems

4D MRI: Robust sorting of free breathing MRI slices for use in interventional settings

no code implementations4 Oct 2019 Gino Gulamhussene, Fabian Joeres, Marko Rak, Maciej Pech, Christian Hansen

Interventional radiologists perceive the reconstruction quality of our method as higher compared to the baseline (262. 5 points vs. 217. 5 points, p=0. 02).

MRI Reconstruction

Variational Hashing-based Collaborative Filtering with Self-Masking

no code implementations25 Sep 2019 Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma

To this end, we propose an end-to-end trainable variational hashing-based collaborative filtering approach that uses the novel concept of self-masking: the user hash code acts as a mask on the items (using the Boolean AND operation), such that it learns to encode which bits are important to the user, rather than the user's preference towards the underlying item property that the bits represent.

Collaborative Filtering

Unsupervised Neural Generative Semantic Hashing

no code implementations3 Jun 2019 Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Stephen Alstrup, Christina Lioma

We present a novel unsupervised generative semantic hashing approach, \textit{Ranking based Semantic Hashing} (RBSH) that consists of both a variational and a ranking based component.

Code Generation Document Ranking +1

Neural Check-Worthiness Ranking with Weak Supervision: Finding Sentences for Fact-Checking

no code implementations20 Mar 2019 Casper Hansen, Christian Hansen, Stephen Alstrup, Jakob Grue Simonsen, Christina Lioma

Automatic fact-checking systems detect misinformation, such as fake news, by (i) selecting check-worthy sentences for fact-checking, (ii) gathering related information to the sentences, and (iii) inferring the factuality of the sentences.

Fact Checking Misinformation

Neural Speed Reading with Structural-Jump-LSTM

1 code implementation ICLR 2019 Christian Hansen, Casper Hansen, Stephen Alstrup, Jakob Grue Simonsen, Christina Lioma

We present Structural-Jump-LSTM: the first neural speed reading model to both skip and jump text during inference.

Modelling Sequential Music Track Skips using a Multi-RNN Approach

1 code implementation20 Mar 2019 Christian Hansen, Casper Hansen, Stephen Alstrup, Jakob Grue Simonsen, Christina Lioma

Modelling sequential music skips provides streaming companies the ability to better understand the needs of the user base, resulting in a better user experience by reducing the need to manually skip certain music tracks.

Sequential skip prediction

Predicting Distresses using Deep Learning of Text Segments in Annual Reports

no code implementations13 Nov 2018 Rastin Matin, Casper Hansen, Christian Hansen, Pia Mølgaard

We develop a model that employs the unstructured textual data in the reports as well, namely the auditors' reports and managements' statements.

Double/Debiased/Neyman Machine Learning of Treatment Effects

no code implementations30 Jan 2017 Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey

A more general discussion and references to the existing literature are available in Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016).

BIG-bench Machine Learning

Program Evaluation and Causal Inference with High-Dimensional Data

no code implementations11 Nov 2013 Alexandre Belloni, Victor Chernozhukov, Ivan Fernández-Val, Christian Hansen

In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE).

Causal Inference

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