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ORCIDMathias Berglund
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2020 – today
- 2024
[i6]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:
MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains. CoRR abs/2407.18961 (2024)
2010 – 2019
- 2019
- [c9]Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola:
Regularizing Trajectory Optimization with Denoising Autoencoders. NeurIPS 2019: 2855-2865 - [i5]Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola:
Regularizing Trajectory Optimization with Denoising Autoencoders. CoRR abs/1903.11981 (2019) - 2017
- [b1]Mathias Berglund:
Unsupervised Networks, Stochasticity and Optimization in Deep Learning. Aalto University, Helsinki, Finland, 2017 - 2016
- [c8]Mathias Berglund:
Stochastic gradient estimate variance in contrastive divergence and persistent contrastive divergence. ESANN 2016 - [c7]Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff:
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. ICML 2016: 2952-2960 - [c6]Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber:
Tagger: Deep Unsupervised Perceptual Grouping. NIPS 2016: 4484-4492 - [i4]Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Jürgen Schmidhuber, Harri Valpola:
Tagger: Deep Unsupervised Perceptual Grouping. CoRR abs/1606.06724 (2016) - 2015
- [j1]Mathias Berglund, Tapani Raiko
, KyungHyun Cho:
Measuring the usefulness of hidden units in Boltzmann machines with mutual information. Neural Networks 64: 12-18 (2015) - [c5]Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen:
Bidirectional Recurrent Neural Networks as Generative Models. NIPS 2015: 856-864 - [c4]Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko:
Semi-supervised Learning with Ladder Networks. NIPS 2015: 3546-3554 - [c3]Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh:
Techniques for Learning Binary Stochastic Feedforward Neural Networks. ICLR (Poster) 2015 - [i3]Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen:
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series. CoRR abs/1504.01575 (2015) - [i2]Antti Rasmus, Harri Valpola, Mikko Honkala, Mathias Berglund, Tapani Raiko:
Semi-Supervised Learning with Ladder Network. CoRR abs/1507.02672 (2015) - [i1]Jelena Luketina, Mathias Berglund, Klaus Greff, Tapani Raiko:
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. CoRR abs/1511.06727 (2015) - 2014
- [c2]Mathias Berglund, Tapani Raiko:
Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence. ICLR (Workshop Poster) 2014 - 2013
- [c1]Mathias Berglund, Tapani Raiko, KyungHyun Cho:
Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information. ICONIP (1) 2013: 482-489
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last updated on 2024-11-15 19:30 CET by the dblp team
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