Mathias Berglund

18 papers A* 2B 1Journal 7Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains. NAACL (Findings) 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
2024	J	`jnl`	MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains. CoRR 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
2019	A*	`conf`	Regularizing Trajectory Optimization with Denoising Autoencoders. NeurIPS Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola
2019	J	`jnl`	Regularizing Trajectory Optimization with Denoising Autoencoders. CoRR Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola
2017	—	`—`	Unsupervised Networks, Stochasticity and Optimization in Deep Learning. Mathias Berglund
2016	A*	`conf`	Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. ICML Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff
2016	B	`conf`	Stochastic gradient estimate variance in contrastive divergence and persistent contrastive divergence. ESANN Mathias Berglund
2016	—	`conf`	Tagger: Deep Unsupervised Perceptual Grouping. NIPS Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber
2016	J	`jnl`	Tagger: Deep Unsupervised Perceptual Grouping. CoRR Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Jürgen Schmidhuber, Harri Valpola
2015	J	`jnl`	Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series. CoRR Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen
2015	—	`conf`	Bidirectional Recurrent Neural Networks as Generative Models. NIPS Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen
2015	J	`jnl`	Measuring the usefulness of hidden units in Boltzmann machines with mutual information. Neural Networks Mathias Berglund, Tapani Raiko, Kyunghyun Cho
2015	J	`jnl`	Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. CoRR Jelena Luketina, Mathias Berglund, Klaus Greff, Tapani Raiko
2015	J	`jnl`	Semi-Supervised Learning with Ladder Network. CoRR Antti Rasmus, Harri Valpola, Mikko Honkala, Mathias Berglund, Tapani Raiko
2015	—	`conf`	Semi-supervised Learning with Ladder Networks. NIPS Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko
2015	—	`conf`	Techniques for Learning Binary Stochastic Feedforward Neural Networks. ICLR (Poster) Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh
2014	—	`conf`	Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence. ICLR (Workshop Poster) Mathias Berglund, Tapani Raiko
2013	—	`conf`	Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information. ICONIP (1) Mathias Berglund, Tapani Raiko, Kyunghyun Cho