NIPS Proceedingsβ

Jürgen Schmidhuber

17 Papers

  • Neural Expectation Maximization (2017)
  • Tagger: Deep Unsupervised Perceptual Grouping (2016)
  • Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation (2015)
  • Training Very Deep Networks (2015)
  • Deep Networks with Internal Selective Attention through Feedback Connections (2014)
  • Compete to Compute (2013)
  • Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images (2012)
  • Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices (2010)
  • Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks (2008)
  • Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks (2007)
  • Bias-Optimal Incremental Problem Solving (2002)
  • Source Separation as a By-Product of Regularization (1998)
  • LSTM can Solve Hard Long Time Lag Problems (1996)
  • Predictive Coding with Neural Nets: Application to Text Compression (1994)
  • SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA (1994)
  • Learning Unambiguous Reduced Sequence Descriptions (1991)
  • Reinforcement Learning in Markovian and Non-Markovian Environments (1990)