Mathias Berglund

1. Semi-Supervised Learning with Ladder Networks
   2015/07/09 by Antti Rasmus, Harri Valpola, Rasmus, Antti +7 · 45 citations
   Computer Science · #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
2. Tagger: Deep Unsupervised Perceptual Grouping
   2016/06/21 by Klaus Greff, Antti Rasmus, Greff, Klaus +9 · 3 citations
   Computer Science · #97R40 #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Neural and Evolutionary Computing (cs.NE)
3. Techniques for Learning Binary Stochastic Feedforward Neural Networks
   2014/06/11 by Tapani Raiko, Mathias Berglund, Raiko, Tapani +5 · 3 citations
   Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
4. MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains
   2024/07/18 by Guoli Yin, Yin, Guoli, Haoping Bai +44 · 5 citations
   Computer Science · #Multi-Agent Systems and Negotiation #AI-based Problem Solving and Planning #Semantic Web and Ontologies
5. Stochastic Gradient Estimate Variance in Contrastive Divergence and\n Persistent Contrastive Divergence
   2013/12/20 by Mathias Berglund, Tapani Raiko, Berglund, Mathias +1 · 1 citation
   Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #62M45 #Advanced Electron Microscopy Techniques and Applications #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural and Evolutionary Computing (cs.NE) #Stochastic Gradient Optimization Techniques
6. Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series
   2015/04/07 by Mathias Berglund, Berglund, Mathias, Tapani Raiko +9 · 1 citation
   Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Music and Audio Processing #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Time Series Analysis and Forecasting