Mathias Berglund

According to our database, Mathias Berglund authored at least 13 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains.

Guoli Yin, Haoping Bai, Shuang Ma, Feng Nan, Yanchao Sun, Zhaoyang Xu, Shen Ma, Jiarui Lu, Xiang Kong, Aonan Zhang, Dian Ang Yap, Yizhe Zhang, Karsten Ahnert, Vik Kamath, Mathias Berglund, Dominic Walsh, Tobias Gindele, Juergen Wiest, Zhengfeng Lai, Xiaoming Wang, Jiulong Shan, Meng Cao, Ruoming Pang, Zirui Wang

CoRR, 2024

2019

Regularizing Trajectory Optimization with Denoising Autoencoders.

Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Unsupervised Networks, Stochasticity and Optimization in Deep Learning.

Mathias Berglund

PhD thesis, 2017

2016

Tagger: Deep Unsupervised Perceptual Grouping.

Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters.

Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff

Proceedings of the 33nd International Conference on Machine Learning, 2016

Stochastic gradient estimate variance in contrastive divergence and persistent contrastive divergence.

Mathias Berglund

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Measuring the usefulness of hidden units in Boltzmann machines with mutual information.

Mathias Berglund, Tapani Raiko, KyungHyun Cho

Neural Networks, 2015

Semi-Supervised Learning with Ladder Network.

Antti Rasmus, Harri Valpola, Mikko Honkala, Mathias Berglund, Tapani Raiko

CoRR, 2015

Techniques for Learning Binary Stochastic Feedforward Neural Networks.

Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh

Proceedings of the 3rd International Conference on Learning Representations, 2015

Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series.

Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen

CoRR, 2015

Semi-supervised Learning with Ladder Networks.

Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bidirectional Recurrent Neural Networks as Generative Models.

Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence.

Mathias Berglund, Tapani Raiko

Proceedings of the 2nd International Conference on Learning Representations, 2014