Deep Belief Nets for Topic Modeling. - Lars Maaloe; Morten Arngren; Ole Winther (CoRR, 2015)

Recurrent Spatial Transformer Networks. - Søren Kaae Sønderby; Casper Kaae Sønderby; Lars Maaløe; Ole Winther (CoRR, 2015)

Auxiliary Deep Generative Models. - Lars Maaløe; Casper Kaae Sønderby; Søren Kaae Sønderby; Ole Winther (ICML, 2016)

Ladder Variational Autoencoders. - Casper Kaae Sønderby; Tapani Raiko; Lars Maaløe; Søren Kaae Sønderby; Ole Winther (NIPS, 2016)

How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. - Casper Kaae Sønderby; Tapani Raiko; Lars Maaløe; Søren Kaae Sønderby; Ole Winther (CoRR, 2016)

Semi-Supervised Generation with Cluster-aware Generative Models. - Lars Maaløe; Marco Fraccaro; Ole Winther (CoRR, 2017)

Exploiting Nontrivial Connectivity for Automatic Speech Recognition. - Marius Paraschiv; Lasse Borgholt; Tycho Max Sylvester Tax; Marco Singh; Lars Maaløe (CoRR, 2017)

Utilizing Domain Knowledge in End-to-End Audio Processing. - Tycho Max Sylvester Tax; Jose Luis Diez Antich; Hendrik Purwins; Lars Maaløe (CoRR, 2017)

On the Inductive Bias of Word-Character-Level Multi-Task Learning for Speech Recognition. - Jan Kremer; Lasse Borgholt; Lars Maaløe (CoRR, 2018)

Deep Generative Models for Semi-Supervised Machine Learning. - Lars Maaløe (2018)

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. - Lars Maaløe; Marco Fraccaro; Valentin Liévin; Ole Winther (NeurIPS, 2019)

MultiQT: Multimodal learning for real-time question tracking in speech. - Jakob D. Havtorn; Jan Latko; Joakim Edin; Lars Maaløe; Lasse Borgholt; Lorenzo Belgrano; Nicolai Jacobsen; Regitze Sdun; Zeljko Agic (ACL, 2020)

Do End-to-End Speech Recognition Models Care About Context? - Lasse Borgholt; Jakob D. Havtorn; Zeljko Agic; Anders Søgaard; Lars Maaløe; Christian Igel (INTERSPEECH, 2020)

MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech. - Jakob D. Havtorn; Jan Latko; Joakim Edin; Lasse Borgholt; Lars Maaløe; Lorenzo Belgrano; Nicolai F. Jakobsen; Regitze Sdun; Zeljko Agic (CoRR, 2020)

On Scaling Contrastive Representations for Low-Resource Speech Recognition. - Lasse Borgholt; Tycho M. S. Tax; Jakob D. Havtorn; Lars Maaløe; Christian Igel (ICASSP, 2021)

Hierarchical VAEs Know What They Don't Know. - Jakob Drachmann Havtorn; Jes Frellsen; Søren Hauberg; Lars Maaløe (ICML, 2021)

Do We Still Need Automatic Speech Recognition for Spoken Language Understanding? - Lasse Borgholt; Jakob Drachmann Havtorn; Mostafa Abdou; Joakim Edin; Lars Maaløe; Anders Søgaard; Christian Igel (CoRR, 2021)

Model-agnostic out-of-distribution detection using combined statistical tests. - Federico Bergamin; Pierre-Alexandre Mattei; Jakob Drachmann Havtorn; Hugo Sénétaire; Hugo Schmutz; Lars Maaløe; Søren Hauberg; Jes Frellsen (AISTATS, 2022)

Benchmarking Generative Latent Variable Models for Speech. - Jakob D. Havtorn; Lasse Borgholt; Søren Hauberg; Jes Frellsen; Lars Maaløe (CoRR, 2022)

A Brief Overview of Unsupervised Neural Speech Representation Learning. - Lasse Borgholt; Jakob Drachmann Havtorn; Joakim Edin; Lars Maaløe; Christian Igel (CoRR, 2022)

Self-Supervised Speech Representation Learning: A Review. - Abdelrahman Mohamed; Hung-yi Lee; Lasse Borgholt; Jakob D. Havtorn; Joakim Edin; Christian Igel; Katrin Kirchhoff; Shang-Wen Li 001; Karen Livescu; Lars Maaløe; Tara N. Sainath; Shinji Watanabe 001 (IEEE J. Sel. Top. Signal Process., 2022)

Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study. - Joakim Edin; Alexander Junge; Jakob D. Havtorn; Lasse Borgholt; Maria Maistro; Tuukka Ruotsalo; Lars Maaløe (SIGIR, 2023)

A retrospective study on machine learning-assisted stroke recognition for medical helpline calls. - Jonathan Wenstrup; Jakob Drachmann Havtorn; Lasse Borgholt; Stig Nikolaj Blomberg; Lars Maaloe; Michael R. Sayre; Hanne Christensen; Christina Kruuse; Helle Collatz Christensen (npj Digit. Medicine, 2023)

An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records. - Joakim Edin; Maria Maistro; Lars Maaløe; Lasse Borgholt; Jakob D. Havtorn; Tuukka Ruotsalo (EMNLP, 2024)

Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attribution Explainability. - Joakim Edin; Andreas Geert Motzfeldt; Casper L. Christensen; Tuukka Ruotsalo; Lars Maaløe; Maria Maistro (CoRR, 2024)

Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attributions Explainability. - Joakim Edin; Andreas Geert Motzfeldt; Casper L. Christensen; Tuukka Ruotsalo; Lars Maaløe; Maria Maistro (ACL (1), 2025)

FactsR: A Safer Method for Producing High Quality Healthcare Documentation. - Victor Petrén Bach Hansen; Lasse Krogsbøll; Jonas Lyngsø; Mathias Baltzersen; Andreas Geert Motzfeldt; Kevin Pelgrims; Lars Maaløe (CoRR, 2025)

GIM: Improved Interpretability for Large Language Models. - Joakim Edin; Róbert Csordás; Tuukka Ruotsalo; Zhengxuan Wu; Maria Maistro; Jing Huang; Lars Maaløe (CoRR, 2025)