Schmidhuber, Jurgen

141 publications

ICML 2025 Agent-as-a-Judge: Evaluate Agents with Agents Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber

TMLR 2025 Class-Wise Generalization Error: An Information-Theoretic Analysis Firas Laakom, Moncef Gabbouj, Jürgen Schmidhuber, Yuheng Bu

NeurIPS 2025 Curious Causality-Seeking Agents in Open-Ended Worlds Zhiyu Zhao, Haoxuan Li, Haifeng Zhang, Jun Wang, Francesco Faccio, Jürgen Schmidhuber, Mengyue Yang

ICML 2025 Directly Forecasting Belief for Reinforcement Learning with Delays Qingyuan Wu, Yuhui Wang, Simon Sinong Zhan, Yixuan Wang, Chung-Wei Lin, Chen Lv, Qi Zhu, Jürgen Schmidhuber, Chao Huang

ICLR 2025 FACTS: A Factored State-Space Framework for World Modelling Li Nanbo, Firas Laakom, Yucheng Xu, Wenyi Wang, Jürgen Schmidhuber

ICML 2025 Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective Firas Laakom, Haobo Chen, Jürgen Schmidhuber, Yuheng Bu

TMLR 2025 Faster Diffusion Through Temporal Attention Decomposition Haozhe Liu, Wentian Zhang, Jinheng Xie, Francesco Faccio, Mengmeng Xu, Tao Xiang, Mike Zheng Shou, Juan-Manuel Perez-Rua, Jürgen Schmidhuber

TMLR 2025 MarDini: Masked Auto-Regressive Diffusion for Video Generation at Scale Haozhe Liu, Shikun Liu, Zijian Zhou, Mengmeng Xu, Yanping Xie, Xiao Han, Juan Camilo Perez, Ding Liu, Kumara Kahatapitiya, Menglin Jia, Jui-Chieh Wu, Sen He, Tao Xiang, Jürgen Schmidhuber, Juan-Manuel Perez-Rua

ICML 2025 Measuring In-Context Computation Complexity via Hidden State Prediction Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

ICLRW 2025 Measuring In-Context Computation Complexity via Hidden State Prediction Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

TMLR 2025 Metalearning Continual Learning Algorithms Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

NeurIPS 2025 PhysGym: Benchmarking LLMs in Interactive Physics Discovery with Controlled Priors Yimeng Chen, Piotr Piękos, Mateusz Ostaszewski, Firas Laakom, Jürgen Schmidhuber

ICML 2025 Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning Yuhui Wang, Qingyuan Wu, Dylan R. Ashley, Francesco Faccio, Weida Li, Chao Huang, Jürgen Schmidhuber

ICMLW 2024 Accelerating the Inference of String Generation-Based Chemical Reaction Models for Industrial Applications Mikhail Andronov, Natalia Andronova, Michael Wand, Djork-Arné Clevert, Jürgen Schmidhuber

ICML 2024 Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays Qingyuan Wu, Simon Sinong Zhan, Yixuan Wang, Yuhui Wang, Chung-Wei Lin, Chen Lv, Qi Zhu, Jürgen Schmidhuber, Chao Huang

ICLR 2024 Exploring the Promise and Limits of Real-Time Recurrent Learning Kazuki Irie, Anand Gopalakrishnan, Jürgen Schmidhuber

ICML 2024 GPTSwarm: Language Agents as Optimizable Graphs Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, Jürgen Schmidhuber

ECCV 2024 Goldfish: Vision-Language Understanding of Arbitrarily Long Videos Kirolos Ataallah, Xiaoqian Shen, Eslam mohamed Abdelrahman, Essam Sleiman, Mingchen Zhuge, Jian Ding, Deyao Zhu, Jürgen Schmidhuber, Mohamed Elhoseiny

ICML 2024 Highway Value Iteration Networks Yuhui Wang, Weida Li, Francesco Faccio, Qingyuan Wu, Jürgen Schmidhuber

ICML 2024 Learning Useful Representations of Recurrent Neural Network Weight Matrices Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber

ICLR 2024 MetaGPT: Meta Programming for a Multi-Agent Collaborative Framework Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber

NeurIPS 2024 MoEUT: Mixture-of-Experts Universal Transformers Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber, Christopher Potts, Christopher D. Manning

NeurIPS 2024 Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery Anand Gopalakrishnan, Aleksandar Stanić, Jürgen Schmidhuber, Michael Curtis Mozer

ICML 2024 Sequence Compression Speeds up Credit Assignment in Reinforcement Learning Aditya Ramesh, Kenny John Young, Louis Kirsch, Jürgen Schmidhuber

NeurIPS 2024 SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention Róbert Csordás, Piotr Piękos, Kazuki Irie, Jürgen Schmidhuber

CVPR 2024 Tune-an-Ellipse: CLIP Has Potential to Find What You Want Jinheng Xie, Songhe Deng, Bing Li, Haozhe Liu, Yawen Huang, Yefeng Zheng, Jurgen Schmidhuber, Bernard Ghanem, Linlin Shen, Mike Zheng Shou

ICLRW 2023 Accelerating Neural Self-Improvement via Bootstrapping Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2023 Continually Adapting Optimizers Improve Meta-Generalization Wenyi Wang, Louis Kirsch, Francesco Faccio, Mingchen Zhuge, Jürgen Schmidhuber

NeurIPSW 2023 Continually Adapting Optimizers Improve Meta-Generalization Wenyi Wang, Louis Kirsch, Francesco Faccio, Mingchen Zhuge, Jürgen Schmidhuber

NeurIPS 2023 Contrastive Training of Complex-Valued Autoencoders for Object Discovery Aleksandar Stanić, Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2023 Efficient Value Propagation with the Compositional Optimality Equation Piotr Piękos, Aditya Ramesh, Francesco Faccio, Jürgen Schmidhuber

AAAI 2023 Goal-Conditioned Generators of Deep Policies Francesco Faccio, Vincent Herrmann, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber

ICLR 2023 Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2023 Learning Useful Representations of Recurrent Neural Network Weight Matrices Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber

ICCV 2023 Learning to Identify Critical States for Reinforcement Learning from Videos Haozhe Liu, Mingchen Zhuge, Bing Li, Yuhui Wang, Francesco Faccio, Bernard Ghanem, Jürgen Schmidhuber

NeurIPSW 2023 Mindstorms in Natural Language-Based Societies of Mind Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber

ICML 2023 The Benefits of Model-Based Generalization in Reinforcement Learning Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

ICMLW 2023 Topological Neural Discrete Representation Learning À La Kohonen Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

NeurIPSW 2023 Towards General-Purpose In-Context Learning Agents Louis Kirsch, James Harrison, C. Daniel Freeman, Jascha Sohl-Dickstein, Jürgen Schmidhuber

NeurIPSW 2023 Towards General-Purpose In-Context Learning Agents Louis Kirsch, James Harrison, C. Daniel Freeman, Jascha Sohl-Dickstein, Jürgen Schmidhuber

NeurIPSW 2023 Towards General-Purpose In-Context Learning Agents Louis Kirsch, James Harrison, C. Freeman, Jascha Sohl-Dickstein, Jürgen Schmidhuber

NeurIPSW 2023 Towards General-Purpose In-Context Learning Agents Louis Kirsch, James Harrison, C. Freeman, Jascha Sohl-Dickstein, Jürgen Schmidhuber

ICML 2022 A Modern Self-Referential Weight Matrix That Learns to Modify Itself Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

ICMLW 2022 An Investigation into the Open World Survival Game Crafter Aleksandar Stanić, Yujin Tang, David Ha, Jürgen Schmidhuber

NeurIPS 2022 Exploring Through Random Curiosity with General Value Functions Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

ICMLW 2022 General Policy Evaluation and Improvement by Learning to Identify Few but Crucial States Francesco Faccio, Aditya Ramesh, Vincent Herrmann, Jean Harb, Jürgen Schmidhuber

ICMLW 2022 Goal-Conditioned Generators of Deep Policies Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

NeurIPS 2022 Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules Kazuki Irie, Francesco Faccio, Jürgen Schmidhuber

NeurIPSW 2022 On Narrative Information and the Distillation of Stories Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Jürgen Schmidhuber

AAAI 2022 Reward-Weighted Regression Converges to a Global Optimum Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber

ICMLW 2022 Self-Referential Meta Learning Louis Kirsch, Jürgen Schmidhuber

NeurIPSW 2022 The Benefits of Model-Based Generalization in Reinforcement Learning Kenny John Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

ICML 2022 The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

ICLR 2022 The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2021 A Modern Self-Referential Weight Matrix That Learns to Modify Itself Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

ICLR 2021 Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks Róbert Csordás, Sjoerd van Steenkiste, Jürgen Schmidhuber

NeurIPSW 2021 Augmenting Classic Algorithms with Neural Components for Strong Generalisation on Ambiguous and High-Dimensional Data Imanol Schlag, Jürgen Schmidhuber

NeurIPSW 2021 Exploring Through Random Curiosity with General Value Functions Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

NeurIPS 2021 Going Beyond Linear Transformers with Recurrent Fast Weight Programmers Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

AAAI 2021 Hierarchical Relational Inference Aleksandar Stanic, Sjoerd van Steenkiste, Jürgen Schmidhuber

NeurIPSW 2021 Improving Baselines in the Wild Kazuki Irie, Imanol Schlag, Róbert Csordás, Jürgen Schmidhuber

NeurIPSW 2021 Learning Adaptive Control Flow in Transformers for Improved Systematic Generalization Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber

ICLR 2021 Learning Associative Inference Using Fast Weight Memory Imanol Schlag, Tsendsuren Munkhdalai, Jürgen Schmidhuber

ICML 2021 Linear Transformers Are Secretly Fast Weight Programmers Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber

NeurIPS 2021 Meta Learning Backpropagation and Improving It Louis Kirsch, Jürgen Schmidhuber

ICLR 2021 Parameter-Based Value Functions Francesco Faccio, Louis Kirsch, Jürgen Schmidhuber

ICLR 2021 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann

ICLRW 2021 Training and Generating Neural Networks in Compressed Weight Space Kazuki Irie, Jürgen Schmidhuber

NeurIPSW 2021 Unsupervised Learning of Temporal Abstractions Using Slot-Based Transformers Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber, Sjoerd van Steenkiste

ICLR 2021 Unsupervised Object Keypoint Learning Using Local Spatial Predictability Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber

ICLR 2020 Improving Generalization in Meta Reinforcement Learning Using Learned Objectives Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

ICMLW 2020 Meta-Learning for Recalibration of EMG-Based Upper Limb Prostheses Krsto Proroković, Michael Wand, Jürgen Schmidhuber

NeurIPS 2019 Are Disentangled Representations Helpful for Abstract Visual Reasoning? Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, Olivier Bachem

ICLR 2019 Hindsight Policy Gradients Paulo Rauber, Avinash Ummadisingu, Filipe Mutz, Jürgen Schmidhuber

NeurIPS 2018 Learning to Reason with Third Order Tensor Products Imanol Schlag, Jürgen Schmidhuber

NeurIPS 2018 Recurrent World Models Facilitate Policy Evolution David Ha, Jürgen Schmidhuber

ICLR 2018 Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and Their Interactions Sjoerd van Steenkiste, Michael Chang, Klaus Greff, Jürgen Schmidhuber

ICLR 2017 Highway and Residual Networks Learn Unrolled Iterative Estimation Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber

NeurIPS 2017 Neural Expectation Maximization Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

ICLR 2017 Neural Expectation Maximization Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

ICML 2017 Recurrent Highway Networks Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnı́k, Jürgen Schmidhuber

NeurIPS 2016 Tagger: Deep Unsupervised Perceptual Grouping Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hao, Harri Valpola, Jürgen Schmidhuber

NeurIPS 2015 Parallel Multi-Dimensional LSTM, with Application to Fast Biomedical Volumetric Image Segmentation Marijn F Stollenga, Wonmin Byeon, Marcus Liwicki, Jürgen Schmidhuber

NeurIPS 2015 Training Very Deep Networks Rupesh K Srivastava, Klaus Greff, Jürgen Schmidhuber

ICLR 2015 Understanding Locally Competitive Networks Rupesh Kumar Srivastava, Jonathan Masci, Faustino J. Gomez, Jürgen Schmidhuber

NeurIPS 2014 Deep Networks with Internal Selective Attention Through Feedback Connections Marijn F Stollenga, Jonathan Masci, Faustino Gomez, Jürgen Schmidhuber

JMLR 2014 Natural Evolution Strategies Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber

NeurIPS 2013 Compete to Compute Rupesh K Srivastava, Jonathan Masci, Sohrob Kazerounian, Faustino Gomez, Jürgen Schmidhuber

IJCAI 2013 Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback Hung Quoc Ngo, Matthew David Luciw, Ngo Anh Vien, Jürgen Schmidhuber

NeurIPS 2012 Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images Dan Ciresan, Alessandro Giusti, Luca M. Gambardella, Jürgen Schmidhuber

CVPR 2012 Multi-Column Deep Neural Networks for Image Classification Dan C. Ciresan, Ueli Meier, Jürgen Schmidhuber

ICML 2012 On the Size of the Online Kernel Sparsification Dictionary Yi Sun, Faustino J. Gomez, Jürgen Schmidhuber

IJCAI 2011 Flexible, High Performance Convolutional Neural Networks for Image Classification Dan Claudiu Ciresan, Ueli Meier, Jonathan Masci, Luca Maria Gambardella, Jürgen Schmidhuber

ICML 2011 Incremental Basis Construction from Temporal Difference Error Yi Sun, Faustino J. Gomez, Mark B. Ring, Jürgen Schmidhuber

IJCAI 2011 Incremental Slow Feature Analysis Varun Raj Kompella, Matthew D. Luciw, Jürgen Schmidhuber

ECML-PKDD 2011 Unsupervised Modeling of Partially Observable Environments Vincent Graziano, Jan Koutník, Jürgen Schmidhuber

ECML-PKDD 2010 Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition Somayeh Danafar, Arthur Gretton, Jürgen Schmidhuber

ECML-PKDD 2010 Formal Theory of Fun and Creativity Jürgen Schmidhuber

NeurIPS 2010 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez

JMLR 2010 PyBrain Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber

ICML 2009 Stochastic Search Using the Natural Gradient Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Schmidhuber

JMLR 2008 Accelerated Neural Evolution Through Cooperatively Coevolved Synapses Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen

NeurIPS 2008 Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks Alex Graves, Jürgen Schmidhuber

ECML-PKDD 2008 State-Dependent Exploration for Policy Gradient Methods Thomas Rückstieß, Martin Felder, Jürgen Schmidhuber

IJCAI 2007 Learning Restart Strategies Matteo Gagliolo, Jürgen Schmidhuber

IJCAI 2007 Sequence Labelling in Structured Domains with Hierarchical Recurrent Neural Networks Santiago Fernández, Alex Graves, Jürgen Schmidhuber

ALT 2007 Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity and Creativity Jürgen Schmidhuber

NeurIPS 2007 Unconstrained On-Line Handwriting Recognition with Recurrent Neural Networks Alex Graves, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber, Santiago Fernández

ICML 2006 Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks Alex Graves, Santiago Fernández, Faustino J. Gomez, Jürgen Schmidhuber

ECML-PKDD 2006 Efficient Non-Linear Control Through Neuroevolution Faustino J. Gomez, Jürgen Schmidhuber, Risto Miikkulainen

IJCAI 2005 Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning Jürgen Schmidhuber, Daan Wierstra, Faustino J. Gomez

ECML-PKDD 2004 Adaptive Online Time Allocation to Search Algorithms Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber

MLJ 2004 Optimal Ordered Problem Solver Jürgen Schmidhuber

NeurIPS 2002 Bias-Optimal Incremental Problem Solving Jürgen Schmidhuber

NeCo 2002 Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM Jürgen Schmidhuber, Felix A. Gers, Douglas Eck

JMLR 2002 Learning Precise Timing with LSTM Recurrent Networks Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber

COLT 2002 The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions Jürgen Schmidhuber

NeCo 2000 Learning to Forget: Continual Prediction with LSTM Felix A. Gers, Jürgen Schmidhuber, Fred A. Cummins

NeCo 1999 Feature Extraction Through LOCOCODE Sepp Hochreiter, Jürgen Schmidhuber

ICML 1998 Evolving Structured Programs with Hierarchical Instructions and Skip Nodes Rafal Salustowicz, Jürgen Schmidhuber

MLJ 1998 Fast Online Q(lambda) Marco A. Wiering, Jürgen Schmidhuber

MLJ 1998 Learning Team Strategies: Soccer Case Studies Rafal Salustowicz, Marco A. Wiering, Jürgen Schmidhuber

NeurIPS 1998 Source Separation as a By-Product of Regularization Sepp Hochreiter, Jürgen Schmidhuber

ECML-PKDD 1998 Speeding up Q(lambda)-Learning Marco A. Wiering, Jürgen Schmidhuber

NeCo 1997 Flat Minima Sepp Hochreiter, Jürgen Schmidhuber

NeCo 1997 Long Short-Term Memory Sepp Hochreiter, Jürgen Schmidhuber

ECML-PKDD 1997 Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space Rafal Salustowicz, Jürgen Schmidhuber

MLJ 1997 Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement Jürgen Schmidhuber, Jieyu Zhao, Marco A. Wiering

NeurIPS 1996 LSTM Can Solve Hard Long Time Lag Problems Sepp Hochreiter, Jürgen Schmidhuber

NeCo 1996 Semilinear Predictability Minimization Produces Well-Known Feature Detectors Jürgen Schmidhuber, Martin Eldracher, Bernhard Foltin

ICML 1996 Solving POMDPs with Levin Search and EIRA Marco A. Wiering, Jürgen Schmidhuber

ICML 1995 Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability Jürgen Schmidhuber

NeurIPS 1994 Predictive Coding with Neural Nets: Application to Text Compression Jürgen Schmidhuber, Stefan Heil

NeurIPS 1994 Simplifying Neural Nets by Discovering Flat Minima Sepp Hochreiter, Jürgen Schmidhuber

NeCo 1993 Discovering Predictable Classifications Jürgen Schmidhuber, Daniel Prelinger

NeCo 1992 A Fixed Size Storage O(n3) Time Complexity Learning Algorithm for Fully Recurrent Continually Running Networks Jürgen Schmidhuber

NeCo 1992 Learning Complex, Extended Sequences Using the Principle of History Compression Jürgen Schmidhuber

NeCo 1992 Learning Factorial Codes by Predictability Minimization Jürgen Schmidhuber

NeCo 1992 Learning to Control Fast-Weight Memories: An Alternative to Dynamic Recurrent Networks Jürgen Schmidhuber

NeurIPS 1991 Learning Unambiguous Reduced Sequence Descriptions Jürgen Schmidhuber

NeurIPS 1990 Reinforcement Learning in Markovian and Non-Markovian Environments Jürgen Schmidhuber