Lars Maaløe
Lars Maaløe
Co-Founder & CTO at Corti, PhD in Machine Learning
Verified email at cortilabs.com
Title
Cited by
Cited by
Year
Ladder variational autoencoders
CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther
Advances in Neural Information Processing Systems, 3738-3746, 2016
2942016
Auxiliary deep generative models
L Maaløe, CK Sønderby, SK Sønderby, O Winther
Proceedings of the International Conference on Machine Learning, 2016
2752016
How to train deep variational autoencoders and probabilistic ladder networks
CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther
arXiv preprint arXiv:1602.02282, 2016
722016
Recurrent spatial transformer networks
SK Sønderby, CK Sønderby, L Maaløe, O Winther
arXiv preprint arXiv:1509.05329, 2015
332015
Improving semi-supervised learning with auxiliary deep generative models
L Maaløe, CK Sønderby, SK Sønderby, O Winther
NIPS Workshop on Advances in Approximate Bayesian Inference, 2015
232015
BIVA: A very deep hierarchy of latent variables for generative modeling
L Maaløe, M Fraccaro, V Liévin, O Winther
Advances in Neural Information Processing Systems, 2019
212019
Semi-supervised generation with cluster-aware generative models
L Maaløe, M Fraccaro, O Winther
NIPS Workshop on Advances in Approximate Bayesian Inference, 2017
212017
Deep belief nets for topic modeling
L Maaløe, M Arngren, O Winther
ICML workshop on Knowledge-Powered Deep Learning for Text Mining, 2015
142015
Utilizing Domain Knowledge in End-to-End Audio Processing
TMS Tax, JLD Antich, H Purwins, L Maaløe
NIPS workshop on machine learning for audio, 2017
42017
Development and implementation of a PV performance monitoring system based on inverter measurements
SV Spataru, A Gavriluta, D Sera, L Maaloe, O Winther
2016 IEEE Energy Conversion Congress and Exposition (ECCE), 1-7, 2016
22016
On the Inductive Bias of Word-Character-Level Multi-Task Learning for Speech Recognition
J Kremer, L Borgholt, L Maaløe
NIPS Workshop on Interpretability and Robustness for Audio, Speech and Language, 2018
12018
Condition Monitoring in Photovoltaic Systems by Semi-Supervised Machine Learning
L Maaløe, O Winther, S Spataru, D Sera
Energies 13 (3), 584, 2020
2020
Towards Hierarchical Discrete Variational Autoencoders
V Liévin, A Dittadi, L Maaløe, O Winther
NeurIPS Workshop on Advances in Approximate Bayesian Inference, 2019
2019
Deep Generative Models for Semi-Supervised Machine Learning
L Maaløe
DTU Compute, 2018
2018
Exploiting Nontrivial Connectivity for Automatic Speech Recognition
M Paraschiv, L Borgholt, TMS Tax, M Singh, L Maaløe
NIPS workshop on machine learning for audio, 2017
2017
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