Jürgen Schmidhuber

Luca Maria Gambardella, Jürgen Schmidhuber, Gianni A. Di Caro, 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

Training Recurrent Networks by Evolino

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2007, Neural Computation.

A comparison of algorithms and humans for mitosis detection

Luca Maria Gambardella, Jürgen Schmidhuber, Alessandro Giusti, 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts

Jürgen Schmidhuber, J. Schmidhuber, 2006, Connect. Sci..

A Natural Evolution Strategy for Multi-objective Optimization

Tom Schaul, Jürgen Schmidhuber, Tobias Glasmachers, 2010, PPSN.

Co-evolving recurrent neurons learn deep memory POMDPs

Jürgen Schmidhuber, Faustino J. Gomez, J. Schmidhuber, 2005, GECCO '05.

The neural bucket brigade

Jürgen Schmidhuber, J. Schmidhuber, 1989 .

Convolutional Neural Network Committees for Handwritten Character Classification

Luca Maria Gambardella, Jürgen Schmidhuber, Ueli Meier, 2011, 2011 International Conference on Document Analysis and Recognition.

Highway Networks pdf

Jürgen Schmidhuber, Klaus Greff, Rupesh Kumar Srivastava, 2015, ArXiv.

Hierarchies of Generalized Kolmogorov Complexities and Nonenumerable Universal Measures Computable in the Limit

Jürgen Schmidhuber, J. Schmidhuber, 2002, Int. J. Found. Comput. Sci..

An Anti-hebbian Learning Rule to Represent Drive Motivations for Reinforcement Learning

Jürgen Schmidhuber, Varun Raj Kompella, Sohrob Kazerounian, 2014, SAB.

Framewise phoneme classification with bidirectional LSTM and other neural network architectures

Jürgen Schmidhuber, Alex Graves, J. Schmidhuber, 2005, Neural Networks.

High-Performance Neural Networks for Visual Object Classification pdf

Luca Maria Gambardella, Jürgen Schmidhuber, Jonathan Masci, 2011, ArXiv.

Bias-Optimal Incremental Problem Solving

Jürgen Schmidhuber, J. Schmidhuber, 2002, NIPS.

Hierarchical reinforcement learning with subpolicies specializing for learned subgoals

Jürgen Schmidhuber, Bram Bakker, J. Schmidhuber, 2004, Neural Networks and Computational Intelligence.

Learning to Forget: Continual Prediction with LSTM

Jürgen Schmidhuber, Fred A. Cummins, Felix A. Gers, 2000, Neural Computation.

Evolving large-scale neural networks for vision-based reinforcement learning

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2013, GECCO '13.

One Big Net For Everything pdf

Jürgen Schmidhuber, J. Schmidhuber, 2018, ArXiv.

Improving Speaker-Independent Lipreading with Domain-Adversarial Training

Jürgen Schmidhuber, Michael Wand, J. Schmidhuber, 2017, INTERSPEECH.

Jürgen Schmidhuber, Alexander M. Bronstein, Jonathan Masci, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement

Jürgen Schmidhuber, Jieyu Zhao, Marco Wiering, 1997, Machine Learning.

Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets

Jürgen Schmidhuber, Douglas Eck, Felix A. Gers, 2003, Neural Networks.

Evolving Modular Fast-Weight Networks for Control

Jürgen Schmidhuber, Faustino J. Gomez, J. Schmidhuber, 2005, ICANN.

Optimal Curiosity-Driven Modular Incremental Slow Feature Analysis

Jürgen Schmidhuber, Marijn F. Stollenga, Varun Raj Kompella, 2016, Neural Computation.

A novel unsupervised classification method

Jürgen Schmidhuber, D. Prelinger, 1993 .

Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability

Jürgen Schmidhuber, 1995, ICML.

Flat Minima

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1997, Neural Computation.

Optimal Direct Policy Search

Jürgen Schmidhuber, Tobias Glasmachers, 2011, AGI.

Simple algorithmic theory of subjective beauty, novelty, surprise, interestingness, attention, curiosity, creativity, art, science, music, jokes (特集高次機能の学習と創発--脳・ロボット・人間研究における新たな展開)

Jürgen Schmidhuber, J. Schmidhuber, 2009 .

Learning tactile skills through curious exploration

Jürgen Schmidhuber, Christian Cipriani, Alexander Förster, 2012, Front. Neurorobot..

Lipreading with long short-term memory

Jürgen Schmidhuber, Jan Koutník, Michael Wand, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback

Jürgen Schmidhuber, Matthew D. Luciw, Ngo Anh Vien, 2013, IJCAI.

A scalable neural network architecture for board games

Tom Schaul, Jürgen Schmidhuber, J. Schmidhuber, 2008, 2008 IEEE Symposium On Computational Intelligence and Games.

AutoIncSFA and vision-based developmental learning for humanoid robots

Jürgen Schmidhuber, Mikhail Frank, Jonathan Masci, 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

Completely Self-referential Optimal Reinforcement Learners

Jürgen Schmidhuber, J. Schmidhuber, 2005, ICANN.

An EM Based Training Algorithm for Recurrent Neural Networks

Yi Sun, Jürgen Schmidhuber, Jan Unkelbach, 2009, ICANN.

Language identification from prosody without explicit features

Jürgen Schmidhuber, Fred A. Cummins, Felix A. Gers, 1999, EUROSPEECH.

Binding via Reconstruction Clustering pdf

Jürgen Schmidhuber, Klaus Greff, Rupesh Kumar Srivastava, 2015, ArXiv.

An Integrated, Modular Framework for Computer Vision and Cognitive Robotics Research (icVision)

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2012, BICA.

Driven by Compression Progress

Jürgen Schmidhuber, J. Schmidhuber, 2008, KES.

Artificial General Intelligence - 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3-6, 2011. Proceedings

Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks, 2011, AGI.

On the Size of the Online Kernel Sparsification Dictionary pdf

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2012, ICML.

Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks

Jürgen Schmidhuber, Marcus Liwicki, Horst Bunke, 2007, NIPS.

Modular Value Iteration through Regional Decomposition

Jürgen Schmidhuber, Matthew D. Luciw, Linus Gisslén, 2012, AGI.

A Family of Gödel Machine Implementations

Jürgen Schmidhuber, Bas R. Steunebrink, J. Schmidhuber, 2011, AGI.

Modeling systems with internal state using evolino

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, GECCO '05.

Sequence Labelling in Structured Domains with Hierarchical Recurrent Neural Networks

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2007, IJCAI.

Gödel Machines: Towards a Technical Justification of Consciousness

Jürgen Schmidhuber, J. Schmidhuber, 2005, Adaptive Agents and Multi-Agent Systems.

Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2005, ICANN.

Colossus was the first electronic digital computer

Jürgen Schmidhuber, 2006, Nature.

A Fixed Size Storage O(n3) Time Complexity Learning Algorithm for Fully Recurrent Continually Running Networks

Jürgen Schmidhuber, J. Schmidhuber, 1992, Neural Computation.

Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot pdf

Jürgen Schmidhuber, Marcus Hutter, Faustino J. Gomez, 2006, IAS.

Complexity Monotone in Conditions and Future Prediction Errors

Jürgen Schmidhuber, Marcus Hutter, Alexey V. Chernov, 2006, Kolmogorov Complexity and Applications.

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2006, ICML.

Unsupervised Coding with LOCOCODE

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1997, ICANN.

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition pdf

Luca Maria Gambardella, Jürgen Schmidhuber, Ueli Meier, 2010, ArXiv.

Transfer learning for Latin and Chinese characters with Deep Neural Networks

Jürgen Schmidhuber, Ueli Meier, Dan C. Ciresan, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Kernel representations for evolving continuous functions

Jürgen Schmidhuber, Jan Koutník, Tobias Glasmachers, 2012, Evol. Intell..

Learning to Generate Artificial Fovea Trajectories for Target Detection

Jürgen Schmidhuber, Rudolf Huber, J. Schmidhuber, 1991, Int. J. Neural Syst..

Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity

Jürgen Schmidhuber, J. Schmidhuber, 2007, ALT.

Sequential Constant Size Compressors for Reinforcement Learning

Jürgen Schmidhuber, Matthew D. Luciw, Linus Gisslén, 2011, AGI.

Generating diverse opponents with multiobjective evolution

Julian Togelius, Simon M. Lucas, Jürgen Schmidhuber, 2008, 2008 IEEE Symposium On Computational Intelligence and Games.

Scalable Neural Networks for Board Games

Tom Schaul, Jürgen Schmidhuber, 2009, ICANN.

The IM-CLeVeR Project : Intrinsically Motivated Cumulative Learning Versatile Robots

Julian Togelius, Francesco Mannella, Jürgen Schmidhuber, 2009 .

Efficient natural evolution strategies

Tom Schaul, Yi Sun, Jürgen Schmidhuber, 2009, GECCO.

Rapid Humanoid Motion Learning through Coordinated, Parallel Evolution

Jürgen Schmidhuber, Marijn F. Stollenga, Faustino J. Gomez, 2014, SAB.

New Millennium AI and the Convergence of History: Update of 2012

Jürgen Schmidhuber, J. Schmidhuber, Jürgen Schmidhuber, 2012 .

Efficient Interactive Multiclass Learning from Binary Feedback

Jürgen Schmidhuber, Alexander Förster, Matthew D. Luciw, 2014, TIIS.

Impact of Censored Sampling on the Performance of Restart Strategies

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2006, CP.

Flexible, High Performance Convolutional Neural Networks for Image Classification

Luca Maria Gambardella, Jürgen Schmidhuber, Jonathan Masci, 2011, IJCAI.

Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs pdf

Luca Maria Gambardella, Jürgen Schmidhuber, Ueli Meier, 2011, ArXiv.

Policy Gradient Critics

Jürgen Schmidhuber, Daan Wierstra, J. Schmidhuber, 2007, ECML.

Efficient model-based exploration

Jürgen Schmidhuber, Marco Wiering, J. Schmidhuber, 1998 .

Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2010, NIPS.

Optimal Ordered Problem Solver

Jürgen Schmidhuber, J. Schmidhuber, 2002, Machine Learning.

Nonlinear ICA through low-complexity autoencoders

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).

The New AI: General & Sound & Relevant for Physics

Jürgen Schmidhuber, J. Schmidhuber, 2003, Artificial General Intelligence.

Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images

Luca Maria Gambardella, Jürgen Schmidhuber, Alessandro Giusti, 2012, NIPS.

Learning to Control Fast-Weight Memories: An Alternative to Dynamic Recurrent Networks

Jürgen Schmidhuber, J. Schmidhuber, 1992, Neural Computation.

Predictive Coding with Neural Nets: Application to Text Compression

Jürgen Schmidhuber, Stefan Heil, J. Schmidhuber, 1994, NIPS.

Recurrent World Models Facilitate Policy Evolution

Jürgen Schmidhuber, David Ha, J. Schmidhuber, 2018, NeurIPS.

Explore to see, learn to perceive, get the actions for free: SKILLABILITY

Jürgen Schmidhuber, Marijn F. Stollenga, Varun Raj Kompella, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Reinforcement Learning in Markovian and Non-Markovian Environments

Jürgen Schmidhuber, J. Schmidhuber, 1990, NIPS.

World Models pdf

Jürgen Schmidhuber, David Ha, J. Schmidhuber, 2018, ArXiv.

Autocatalytic endogenous reflective architecture

Jürgen Schmidhuber, Antonio Chella, Giovanni Pezzulo, 2013 .

Classifying Unprompted Speech by Retraining LSTM Nets

Jürgen Schmidhuber, Alex Graves, Nicole Beringer, 2005, ICANN.

An Application of Recurrent Neural Networks to Discriminative Keyword Spotting

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2007, ICANN.

Robust Texture Recognition Using Credal Classifiers

Jürgen Schmidhuber, Alessandro Giusti, Davide Migliore, 2010, BMVC.

Fast Color-Based Object Recognition Independent of Position and Orientation

Jürgen Schmidhuber, Martijn van de Giessen, 2005, ICANN.

Transferring spatial perception between robots operating in a shared workspace

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Neural processing of complex continual input streams

Jürgen Schmidhuber, Felix A. Gers, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Efficient Non-linear Control Through Neuroevolution

Risto Miikkulainen, Jürgen Schmidhuber, Faustino J. Gomez, 2006, ECML.

Learning to Reason with Third-Order Tensor Products

Jürgen Schmidhuber, Imanol Schlag, J. Schmidhuber, 2018, NeurIPS.

2006: Celebrating 75 Years of AI - History and Outlook: The Next 25 Years

Jürgen Schmidhuber, 2006, 50 Years of Artificial Intelligence.

Turing: Keep his work in perspective

Jürgen Schmidhuber, J. Schmidhuber, 2012, Nature.

Gradient-based Reinforcement Planning in Policy-Search Methods

Jürgen Schmidhuber, Marcus Hutter, Ivo Kwee, 2001, ArXiv.

Exploring the predictable

Jürgen Schmidhuber, J. Schmidhuber, 2003 .

Algorithm portfolio selection as a bandit problem with unbounded losses

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2011, Annals of Mathematics and Artificial Intelligence.

Better Digit Recognition with a Committee of Simple Neural Nets

Luca Maria Gambardella, Jürgen Schmidhuber, Ueli Meier, 2011, 2011 International Conference on Document Analysis and Recognition.

The Natural Gradient as a control signal for a humanoid robot

Jürgen Schmidhuber, Marijn F. Stollenga, Alan J. Lockett, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Evolving Memory Cell Structures for Sequence Learning

Julian Togelius, Jürgen Schmidhuber, Justin Bayer, 2009, ICANN.

A Wavelet-based Encoding for Neuroevolution

Jürgen Schmidhuber, Kurt Driessens, Jan Koutník, 2016, GECCO.

Learning the Long-Term Structure of the Blues

Jürgen Schmidhuber, Douglas Eck, J. Schmidhuber, 2002, ICANN.

On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models pdf

Jürgen Schmidhuber, J. Schmidhuber, 2015, ArXiv.

Accelerated Neural Evolution through Cooperatively Coevolved Synapses

Risto Miikkulainen, Jürgen Schmidhuber, Faustino J. Gomez, 2008, J. Mach. Learn. Res..

Discovering Boolean Gates in Slime Mould pdf

Jürgen Schmidhuber, Andrew Adamatzky, Jan Koutník, 2016, ArXiv.

Incremental Slow Feature Analysis: Adaptive Low-Complexity Slow Feature Updating from High-Dimensional Input Streams

Jürgen Schmidhuber, Varun Raj Kompella, Matthew D. Luciw, 2012, Neural Computation.

Phoneme recognition in TIMIT with BLSTM-CTC pdf

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2008, ArXiv.

Compressed Network Complexity Search

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, PPSN.

Using data compressors to construct order tests for homogeneity and component independence

Jürgen Schmidhuber, Daniil Ryabko, 2009, Appl. Math. Lett..

Algorithmic complexity bounds on future prediction errors pdf

Jürgen Schmidhuber, Marcus Hutter, Alexey V. Chernov, 2007, Inf. Comput..

A committee of neural networks for traffic sign classification

Jürgen Schmidhuber, Jonathan Masci, Ueli Meier, 2011, The 2011 International Joint Conference on Neural Networks.

A Frequency-Domain Encoding for Neuroevolution pdf

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, ArXiv.

Continually adding self-invented problems to the repertoire: First experiments with POWERPLAY

Jürgen Schmidhuber, Marijn F. Stollenga, Bas R. Steunebrink, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Learning Restart Strategies

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2007, IJCAI.

A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks

Jürgen Schmidhuber, Alois Knoll, Faustino J. Gomez, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Using Data Compressors to Construct Rank Tests pdf

Jürgen Schmidhuber, Daniil Ryabko, 2007, ArXiv.

Incremental Basis Construction from Temporal Difference Error

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2011, ICML.

Erratum to: Novel Kernel-Based Recognizers of Human Actions

Jürgen Schmidhuber, Alessandro Giusti, Somayeh Danafar, 2012, EURASIP J. Adv. Signal Process..

Autonomous Acquisition of Natural Situated Communication

Jürgen Schmidhuber, Antonio Chella, Giovanni Pezzulo, 2014 .

Task-relevant roadmaps: A framework for humanoid motion planning

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning dynamic algorithm portfolios

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2006, Annals of Mathematics and Artificial Intelligence.

Multimodal Parameter-exploring Policy Gradients

Frank Sehnke, Christian Osendorfer, Jürgen Schmidhuber, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Complexity search for compressed neural networks

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, GECCO '12.

Episodic Reinforcement Learning by Logistic Reward-Weighted Regression

Tom Schaul, Jürgen Schmidhuber, Jan Peters, 2008, ICANN.

Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM

Jürgen Schmidhuber, Douglas Eck, Felix A. Gers, 2002, Neural Computation.

Autonomous learning of robust visual object detection and identification on a humanoid

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Source Separation as a By-Product of Regularization

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1998, NIPS.

Reinforcement learning in partially observable mobile robot domains using unsupervised event extraction

Jürgen Schmidhuber, Bram Bakker, Fredrik Linåker, 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction

Jürgen Schmidhuber, Jonathan Masci, Ueli Meier, 2011, ICANN.

Understanding Locally Competitive Networks pdf

Jürgen Schmidhuber, Jonathan Masci, Faustino J. Gomez, 2014, ICLR.

Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity pdf

Jürgen Schmidhuber, J. Schmidhuber, 2007, Discovery Science.

Continuous history compression

Jürgen Schmidhuber, Michael C. Mozer, D. Prelinger, 1993 .

Ontogenetic and Phylogenetic Reinforcement Learning

Julian Togelius, Tom Schaul, Jürgen Schmidhuber, 2009, Künstliche Intell..

A Clockwork RNN

Jürgen Schmidhuber, Jan Koutník, Klaus Greff, 2014, ICML.

Anytime Bounded Rationality

Jürgen Schmidhuber, Kristinn R. Thórisson, Bas R. Steunebrink, 2015, AGI.

Reinforcement Learning with Self-Modifying Policies

Jürgen Schmidhuber, Jieyu Zhao, Nicol N. Schraudolph, 1998, Learning to Learn.

Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

Jürgen Schmidhuber, J. Schmidhuber, 2008, ABiALS.

An experiment in automatic game design

Julian Togelius, Jürgen Schmidhuber, J. Schmidhuber, 2008, 2008 IEEE Symposium On Computational Intelligence and Games.

An on-line algorithm for dynamic reinforcement learning and planning in reactive environments

Jürgen Schmidhuber, J. Schmidhuber, 1990, 1990 IJCNN International Joint Conference on Neural Networks.

Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements

Jürgen Schmidhuber, J. Schmidhuber, 2003, ArXiv.

Evolving neural networks in compressed weight space

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2010, GECCO '10.

Autonomous learning of abstractions using Curiosity-Driven Modular Incremental Slow Feature Analysis

Jürgen Schmidhuber, Marijn F. Stollenga, Varun Raj Kompella, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Evolino for recurrent support vector machines pdf

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, ESANN.

Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability

Jürgen Schmidhuber, J. Schmidhuber, 1997, Neural Networks.

Evolving Soccer Strategies

Jürgen Schmidhuber, Marco Wiering, Rafal Salustowicz, 1997, ICONIP.

Evolving large-scale neural networks for vision-based TORCS

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2013, FDG.

Generalized Compressed Network Search

Jürgen Schmidhuber, Faustino J. Gomez, Rupesh Kumar Srivastava, 2012, PPSN.

Active Learning with Adaptive Grids

Jürgen Schmidhuber, Michele Milano, Petros Koumoutsakos, 2001, ICANN.

Dynamic Algorithm Portfolios

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2006, AI&M.

Reinforcement Learning Soccer Teams with Incomplete World Models

Jürgen Schmidhuber, Marco Wiering, Rafal Salustowicz, 1999, Auton. Robots.

Recurrent nets that time and count

Jürgen Schmidhuber, Felix A. Gers, J. Schmidhuber, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Deep Networks with Internal Selective Attention through Feedback Connections

Jürgen Schmidhuber, Marijn F. Stollenga, Jonathan Masci, 2014, NIPS.

An intrinsic value system for developing multiple invariant representations with incremental slowness learning

Jürgen Schmidhuber, Varun Raj Kompella, Matthew D. Luciw, 2013, Front. Neurorobot..

Novel Kernel-Based Recognizers of Human Actions

Jürgen Schmidhuber, Alessandro Giusti, Somayeh Danafar, 2010, EURASIP J. Adv. Signal Process..

Evolving Structured Programs with Hierarchical Instructions and Skip Nodes

Jürgen Schmidhuber, Rafal Salustowicz, J. Schmidhuber, 1998, ICML.

Learning Unambiguous Reduced Sequence Descriptions

Jürgen Schmidhuber, J. Schmidhuber, 1991, NIPS.

Robot Learning with State-Dependent Exploration

Frank Sehnke, Jürgen Schmidhuber, Martin Felder, 2008 .

Human-Robot Cooperation: Fast, Interactive Learning from Binary Feedback

Luca Maria Gambardella, Jürgen Schmidhuber, Gianni A. Di Caro, 2014, 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

Recurrent Highway Networks pdf

Jürgen Schmidhuber, Jan Koutník, Rupesh Kumar Srivastava, 2016, ICML.

Training Very Deep Networks

Jürgen Schmidhuber, Klaus Greff, Rupesh Kumar Srivastava, 2015, NIPS.

Learning skills from play: Artificial curiosity on a Katana robot arm

Jürgen Schmidhuber, Alexander Förster, Matthew D. Luciw, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Evolving strategies for active flow control

Jürgen Schmidhuber, Michele Milano, Petros Koumoutsakos, 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

On Fast Deep Nets for AGI Vision

Jürgen Schmidhuber, Alex Graves, Jonathan Masci, 2011, AGI.

Fast image scanning with deep max-pooling convolutional neural networks

Luca Maria Gambardella, Jürgen Schmidhuber, Jonathan Masci, 2013, 2013 IEEE International Conference on Image Processing.

Towards Distributed Algorithm Portfolios

Jürgen Schmidhuber, Matteo Gagliolo, 2008, DCAI.

Self-Motivated Development Through Rewards for Predictor Errors / Improvements

Jürgen Schmidhuber, J. Schmidhuber, 2005, AAAI 2005.

Parameter-exploring policy gradients

Frank Sehnke, Christian Osendorfer, Jürgen Schmidhuber, 2010, Neural Networks.

Curiosity-driven optimization

Tom Schaul, Yi Sun, Jürgen Schmidhuber, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Market-Based Reinforcement Learning in Partially Observable Worlds

Jürgen Schmidhuber, Marcus Hutter, Ivo Kwee, 2001, ICANN.

Learning Factorial Codes by Predictability Minimization

Jürgen Schmidhuber, J. Schmidhuber, 1992, Neural Computation.

Exponential natural evolution strategies

Tom Schaul, Yi Sun, Jürgen Schmidhuber, 2010, GECCO '10.

MT-CGP: mixed type cartesian genetic programming

Jürgen Leitner, Jürgen Schmidhuber, Simon Harding, 2012, GECCO '12.

Multi-column deep neural network for traffic sign classification

Jürgen Schmidhuber, Jonathan Masci, Ueli Meier, 2012, Neural Networks.

Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, IJCAI.

Max-pooling convolutional neural networks for vision-based hand gesture recognition

Luca Maria Gambardella, Farrukh Nagi, Jürgen Schmidhuber, 2011, 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).

My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013 pdf

Jürgen Schmidhuber, 2013, ArXiv.

DeepScores-A Dataset for Segmentation, Detection and Classification of Tiny Objects

Jürgen Schmidhuber, Marcello Pelillo, Ismail Elezi, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients

Tom Schaul, Frank Sehnke, Jürgen Schmidhuber, 2010, ICANN.

Simplifying Neural Nets by Discovering Flat Minima

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1994, NIPS.

The Modular Behavioral Environment for Humanoids and other Robots (MoBeE)

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2012, ICINCO.

Adaptive Online Time Allocation to Search Algorithms

Jürgen Schmidhuber, Matteo Gagliolo, Viktor Zhumatiy, 2004, ECML.

Feature Extraction Through LOCOCODE

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1999, Neural Computation.

Deep learning in neural networks: An overview

Jürgen Schmidhuber, J. Schmidhuber, 2014, Neural Networks.

Learning what to ignore: Memetic climbing in topology and weight space

Julian Togelius, Jürgen Schmidhuber, Faustino J. Gomez, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Teleoperation of a 7 DOF humanoid robot arm using human arm accelerations and EMG signals

Jürgen Schmidhuber, Alexander Förster, Matthew Luciw, 2014 .

Learning Exploration Policies with Models

Jürgen Schmidhuber, Wiering, 1998 .

Philosophers & Futurists, Catch Up! Response to The Singularity

Jürgen Schmidhuber, J. Schmidhuber, 2012 .

Humanoid learns to detect its own hands

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2013, 2013 IEEE Congress on Evolutionary Computation.

Reflexive Collision Response with Virtual Skin - Roadmap Planning Meets Reinforcement Learning

Jürgen Schmidhuber, Mikhail Frank, Alexander Förster, 2016, ICAART.

Self-organizing nets for optimization

Jürgen Schmidhuber, Michele Milano, Petros Koumoutsakos, 2004, IEEE Transactions on Neural Networks.

Coherence Progress: A Measure of Interestingness Based on Fixed Compressors

Tom Schaul, Jürgen Schmidhuber, Tobias Glasmachers, 2011, AGI.

Long Short-Term Memory

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1997, Neural Computation.

Bounded Seed-AGI

Jürgen Schmidhuber, Kristinn R. Thórisson, Antonio Chella, 2014, AGI.

Deep Neural Network Frontend for Continuous EMG-Based Speech Recognition

Jürgen Schmidhuber, Michael Wand, J. Schmidhuber, 2016, INTERSPEECH.

Testing Hypotheses by Regularized Maximum Mean Discrepancy pdf

Jürgen Schmidhuber, Somayeh Danafar, Paola M. V. Rancoita, 2013, ArXiv.

Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics

Jürgen Schmidhuber, Gregor Schöner, Yulia Sandamirskaya, 2014, SAB.

Bounded Recursive Self-Improvement pdf

Jürgen Schmidhuber, Kristinn R. Thórisson, Antonio Chella, 2013, ArXiv.

Countering Poisonous Inputs with Memetic Neuroevolution

Julian Togelius, Tom Schaul, Jürgen Schmidhuber, 2008, PPSN.

High dimensions and heavy tails for natural evolution strategies

Tom Schaul, Jürgen Schmidhuber, Tobias Glasmachers, 2011, GECCO '11.

Discovering Predictable Classifications

Jürgen Schmidhuber, Daniel Prelinger, 1993, Neural Computation.

Gödel Machines: Fully Self-referential Optimal Universal Self-improvers

Jürgen Schmidhuber, J. Schmidhuber, 2007, Artificial General Intelligence.

On-Chip Electric Waves: An Analog Circuit Approach to Physical Uncloneable Functions

Jürgen Schmidhuber, Ulrich Rührmair, Ulf Schlichtmann, 2009, IACR Cryptol. ePrint Arch..

Descriptor Learning for Omnidirectional Image Matching

Jürgen Schmidhuber, Jonathan Masci, Michael M. Bronstein, 2011, Registration and Recognition in Images and Videos.

LSTM can Solve Hard Long Time Lag Problems

Jürgen Schmidhuber, Sepp Hochreiter, S. Hochreiter, 1996, NIPS.

On Learning Soccer Strategies

Jürgen Schmidhuber, Marco Wiering, Rafal Salustowicz, 1997, ICANN.

Modeling attacks on physical unclonable functions

Srinivas Devadas, Frank Sehnke, Jan Sölter, 2010, CCS '10.

Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks

Jürgen Schmidhuber, Alex Graves, J. Schmidhuber, 2008, NIPS.

Fast Online Q(λ)

Jürgen Schmidhuber, Marco Wiering, J. Schmidhuber, 1998, Machine Learning.

Algorithmic Theories of Everything

Jürgen Schmidhuber, J. Schmidhuber, 2000, ArXiv.

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Jürgen Schmidhuber, Marcus Liwicki, Marijn F. Stollenga, 2015, NIPS.

RNN-based Learning of Compact Maps for Efficient Robot Localization

Jürgen Schmidhuber, Alex Graves, Alexander Förster, 2007, ESANN.

Prefix-Like Complexities and Computability in the Limit

Jürgen Schmidhuber, Alexey V. Chernov, 2006, CiE.

Speeding up Q(lambda)-Learning

Jürgen Schmidhuber, Marco Wiering, 1998, ECML.

Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning

Julian Togelius, Jürgen Schmidhuber, Faustino J. Gomez, 2009, ICANN.

Improving robot vision models for object detection through interaction

Jürgen Leitner, Jürgen Schmidhuber, Alexander Förster, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Exploring parameter space in reinforcement learning

Tom Schaul, Yi Sun, Frank Sehnke, 2010, Paladyn J. Behav. Robotics.

Candidate Sampling for Neuron Reconstruction from Anisotropic Electron Microscopy Volumes

Luca Maria Gambardella, Jürgen Schmidhuber, Matthew Cook, 2014, MICCAI.

Incremental Slow Feature Analysis

Jürgen Schmidhuber, Varun Raj Kompella, Matthew D. Luciw, 2011, IJCAI.

Maximizing Fun by Creating Data with Easily Reducible Subjective Complexity

Jürgen Schmidhuber, J. Schmidhuber, 2013, Intrinsically Motivated Learning in Natural and Artificial Systems.

Deep, Big, Simple Neural Nets for Handwritten Digit Recognition

Luca Maria Gambardella, Jürgen Schmidhuber, Ueli Meier, 2010, Neural Computation.

Proceedings of the 4th international conference on Artificial general intelligence

Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks, 2011 .

Reinforcement and shaping in learning action sequences with neural dynamics

Jürgen Schmidhuber, Gregor Schöner, Yulia Sandamirskaya, 2014, 4th International Conference on Development and Learning and on Epigenetic Robotics.

PowerPlay: Training an Increasingly General Problem Solver by Continually Searching for the Simplest Still Unsolvable Problem

Jürgen Schmidhuber, J. Schmidhuber, 2011, Front. Psychol..

Highway and Residual Networks learn Unrolled Iterative Estimation pdf

Jürgen Schmidhuber, Klaus Greff, Rupesh Kumar Srivastava, 2016, ICLR.

Learning Team Strategies: Soccer Case Studies

Jürgen Schmidhuber, Marco Wiering, Rafal Salustowicz, 1998, Machine Learning.

Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control pdf

Jürgen Schmidhuber, Róbert Csordás, J. Schmidhuber, 2019, ICLR.

Confidence-based progress-driven self-generated goals for skill acquisition in developmental robots

Jürgen Schmidhuber, Alexander Förster, Matthew Luciw, 2013, Front. Psychol..

Reactive reaching and grasping on a humanoid: Towards closing the action-perception loop on the iCub

Jürgen Leitner, Jürgen Schmidhuber, Mikhail Frank, 2014, 2014 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO).

Learning Complex, Extended Sequences Using the Principle of History Compression

Jürgen Schmidhuber, J. Schmidhuber, 1992, Neural Computation.

A fast learning algorithm for image segmentation with max-pooling convolutional networks

Jürgen Schmidhuber, Jonathan Masci, Alessandro Giusti, 2013, 2013 IEEE International Conference on Image Processing.

Modular deep belief networks that do not forget

Jürgen Schmidhuber, Faustino J. Gomez, Leo Pape, 2011, The 2011 International Joint Conference on Neural Networks.

Resource-Bounded Machines are Motivated to be Effective, Efficient, and Curious

Jürgen Schmidhuber, Kristinn R. Thórisson, Jan Koutník, 2013, AGI.

Compete to Compute

Jürgen Schmidhuber, Jonathan Masci, Faustino J. Gomez, 2013, NIPS.

Measuring Intelligence through Games pdf

Julian Togelius, Tom Schaul, Jürgen Schmidhuber, 2011, ArXiv.

Multi-Agent Learning with the Success-Story Algorithm

Jürgen Schmidhuber, Jieyu Zhao, J. Schmidhuber, 1996, ECAI Workshop LDAIS / ICMAS Workshop LIOME.

A robot that reinforcement-learns to identify and memorize important previous observations

Jürgen Schmidhuber, Gabriel Gruener, Bram Bakker, 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

Solving POMDPs with Levin Search and EIRA

Jürgen Schmidhuber, Marco Wiering, J. Schmidhuber, 1996, ICML.

New Millennium AI and the Convergence of History: Update of 2012

Jürgen Schmidhuber, 2012 .

Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks

Luca Maria Gambardella, Jürgen Schmidhuber, Alessandro Giusti, 2013, MICCAI.

Biologically Plausible Speech Recognition with LSTM Neural Nets

Jürgen Schmidhuber, Douglas Eck, Alex Graves, 2004, BioADIT.

A Neural Network Model for Inter-problem Adaptive Online Time Allocation

Jürgen Schmidhuber, Matteo Gagliolo, J. Schmidhuber, 2005, ICANN.

Evolving deep unsupervised convolutional networks for vision-based reinforcement learning

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2014, GECCO.

Super mario evolution

Julian Togelius, Jürgen Schmidhuber, Jan Koutník, 2009, 2009 IEEE Symposium on Computational Intelligence and Games.

Hierarchical controller learning in a First-Person Shooter

Julian Togelius, Jürgen Schmidhuber, Niels van Hoorn, 2009, 2009 IEEE Symposium on Computational Intelligence and Games.

Solving Deep Memory POMDPs with Recurrent Policy Gradients

Jürgen Schmidhuber, Alexander Förster, Jan Peters, 2007, ICANN.

Deep Learning

Jürgen Schmidhuber, J. Schmidhuber, 2015, Encyclopedia of Machine Learning and Data Mining.

Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2011, AGI.

Policy Gradients with Parameter-Based Exploration for Control

Frank Sehnke, Christian Osendorfer, Jürgen Schmidhuber, 2008, ICANN.

First Experiments with PowerPlay

Jürgen Schmidhuber, Bas R. Steunebrink, Rupesh Kumar Srivastava, 2012, Neural networks : the official journal of the International Neural Network Society.

A Formal Theory of Creativity to Model the Creation of Art

Jürgen Schmidhuber, J. Schmidhuber, 2012 .

Evolution of National Nobel Prize Shares in the 20th Century pdf

Jürgen Schmidhuber, J. Schmidhuber, 2010, ArXiv.

Multi-column deep neural networks for image classification

Jürgen Schmidhuber, Ueli Meier, Dan C. Ciresan, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Self-Delimiting Neural Networks pdf

Jürgen Schmidhuber, J. Schmidhuber, 2012, ArXiv.

PUF Modeling Attacks on Simulated and Silicon Data

Srinivas Devadas, Frank Sehnke, Jan Sölter, 2013, IEEE Transactions on Information Forensics and Security.

Reward-Weighted Regression Converges to a Global Optimum pdf

Jürgen Schmidhuber, Rupesh Kumar Srivastava, Dylan R. Ashley, 2021, ArXiv.