1 code implementation • 4 Mar 2024 • Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, Vasilis Syrgkanis
An introduction to the emerging fusion of machine learning and causal inference.
no code implementations • 25 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.
no code implementations • 11 Sep 2021 • Christian Hansen
Sequential modelling entails making sense of sequential data, which naturally occurs in a wide array of domains.
1 code implementation • 12 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.
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.
no code implementations • 8 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).
1 code implementation • 26 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.
1 code implementation • 26 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.
no code implementations • 9 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.
1 code implementation • 22 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.
no code implementations • 25 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.
1 code implementation • 23 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.
1 code implementation • 1 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.
1 code implementation • 17 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.
1 code implementation • 31 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.
no code implementations • 4 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).
no code implementations • 25 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.
no code implementations • IJCNLP 2019 • Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, Jakob Grue Simonsen
We contribute the largest publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification.
1 code implementation • 3 Jun 2019 • Casper Hansen, Christian Hansen, Stephen Alstrup, Jakob Grue Simonsen, Christina Lioma
Word embeddings predict a word from its neighbours by learning small, dense embedding vectors.
no code implementations • 3 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.
1 code implementation • 20 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.
no code implementations • 20 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.
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.
no code implementations • 13 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.
no code implementations • 30 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).
4 code implementations • 30 Jul 2016 • Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, James Robins
Fortunately, this regularization bias can be removed by solving auxiliary prediction problems via ML tools.
no code implementations • 11 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).