H. Jaeger

发表

Discrete-time, discrete-valued observable operator models: a tutorial

H. Jaeger, 2003 .

Reservoir computing approaches to recurrent neural network training

Herbert Jaeger, Mantas Lukosevicius, H. Jaeger, 2009, Comput. Sci. Rev..

Optimization and applications of echo state networks with leaky- integrator neurons

Herbert Jaeger, Mantas Lukosevicius, Dan Popovici, 2007, Neural Networks.

Long Short-Term Memory in Echo State Networks: Details of a Simulation Study

Herbert Jaeger, H. Jaeger, 2012 .

A neurodynamical model for working memory

Razvan Pascanu, Herbert Jaeger, Razvan Pascanu, 2011, Neural Networks.

Identi cation of Behaviors in an Agent's Phase Space

H. Jaeger, 1995 .

Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

Harald Haas, Herbert Jaeger, H. Jaeger, 2004, Science.

Observable operator models II: Interpretable models and model induction

H. Jaeger, Gmd St. Augustin, 1997 .

Modeling and learning continuous-valued stochastic processes with OOMs

H. Jaeger, 2000 .

The''echo state''approach to analysing and training recurrent neural networks

Herbert Jaeger, H. Jaeger, 2001 .

Observable Operator Models for Discrete Stochastic Time Series

Herbert Jaeger, H. Jaeger, 2000, Neural Computation.

Characterizing distributions of stochastic processes by linear operators

H. Jaeger, 1999 .

A short introduction to observable operator models of discrete stochastic processes ∗

H. Jaeger, 1997 .

A short introduction to observable operator models of stochastic processes

H. Jaeger, Schloss Birlinghoven, 1998 .

Smart Decisions by Small Adjustments: Iterating Denoising Autoencoders

H. Jaeger, Dzmitry Bahdanau, 2014 .

Unconventional Information Processing Systems , Novel Hardware : A Tour d ’ Horizon

H. Jaeger, Fatemeh Hadaeghi, Xu He, 2017 .

Can't Get You Out of My Head: A Connectionist Model of Cyclic Rehearsal

Douglas Eck, Herbert Jaeger, H. Jaeger, 2006, ZiF Workshop.

Overview of Reservoir Recipes A survey of new RNN training methods that follow the Reservoir paradigm

H. Jaeger, M. Lukoševičius, 2007 .

Stepping forward through echoes of the past : forecasting with Echo State Networks

H. Jaeger, I. Ilies, O. Kosuchinas, 2007 .

Learning observable operator models via the ES algorithm 1

D. Popovici, H. Jaeger, M. Zhao, 2005 .

Behavior Engineering with "Dual Dynamics" Models and Design Tools

Thomas Christaller, Herbert Jaeger, Paul-Gerhard Plöger, 1999, RoboCup.

Time Warping Invariant Echo State Networks

Mantas Lukoševičius, Dan Popovici, Herbert Jaeger, 2006 .

Special issue on echo state networks and liquid state machines

José Carlos Príncipe, Wolfgang Maass, Herbert Jaeger, 2007, Neural Networks.

Echo state network

Herbert Jaeger, H. Jaeger, 2007, Scholarpedia.

The Error Controlling Algorithm for Learning OOMs

H. Jaeger, M. Zhao, 2007 .

Efficient Estimation of OOMs

Herbert Jaeger, Mingjie Zhao, Andreas Kolling, 2005, NIPS.

Harnessing nonlinearity : predicting chaotic systems and boosting wireless communication . " ( Ref : 1091277 ) Refutation of Second Reviewer ' s Objections

H. Jaeger, 2005 .

A tutorial on training recurrent neural networks, covering BPTT, RTRL, EKF and the "echo state network" approach

H. Jaeger, 2021 .

Action selection for stochastic, delayed reward ?

H. Jaeger, 1999 .

- 1-An Introduction to Dynamic Concept Systems

H. Jaeger, 2011 .

Brains on wheels: Mobile robots for brain research

Herbert Jaeger, H. Jaeger, 1996 .

Transient attractors: Re-recognizable regularities in empirical time series

H. Jaeger, 1996 .

CONCEPTOR-AIDED BACKPROPAGATION

H. Jaeger, 2018 .

Eu Fp7 Amarsi Adaptive Modular Architectures for Rich Motor Skills Technical Report on Describing the Archetype Architectures from Annex 1

H. Jaeger, Jacobs, 2011 .

Dynamic Symbol Systems : An Introduction to the Local Model

H. Jaeger, 1996 .

Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation

Xu He, Herbert Jaeger, H. Jaeger, 2018, ICLR.

Timescales: the choreography of classical and unconventional computing

H. Jaeger, F. Catthoor, 2023, 2301.00893.

Timescales: the choreography of classical and unconventional computing

H. Jaeger, F. Catthoor, 2023, ArXiv.

Discovering multiscale dynamical features with hierarchical Echo State Networks

Herbert Jaeger, H. Jaeger, 2008 .

The Dynamics of Random Difference Equations Is Remodeled by Closed Relations

Herbert Jaeger, Manjunath Gandhi, H. Jaeger, 2014, SIAM J. Math. Anal..

Using Conceptors to Manage Neural Long-Term Memories for Temporal Patterns

Herbert Jaeger, H. Jaeger, 2017, J. Mach. Learn. Res..

Controlling Recurrent Neural Networks by Conceptors pdf

Herbert Jaeger, H. Jaeger, 2014, ArXiv.

A Bound on Modeling Error in Observable Operator Models and an Associated Learning Algorithm

Herbert Jaeger, Mingjie Zhao, Michael R. Thon, 2009, Neural Computation.

Reservoir Computing Trends

Benjamin Schrauwen, Herbert Jaeger, Mantas Lukosevicius, 2012, KI - Künstliche Intelligenz.

Dimensions of Timescales in Neuromorphic Computing Systems pdf

Herbert Jaeger, Giacomo Indiveri, Celestine Preetham Lawrence, 2021, ArXiv.

Re-visiting the echo state property

Stefan J. Kiebel, Herbert Jaeger, Izzet B. Yildiz, 2012, Neural Networks.

Towards a generalized theory comprising digital, neuromorphic and unconventional computing

Herbert Jaeger, H. Jaeger, 2021, Neuromorph. Comput. Eng..

Exploring the landscapes of "computing": digital, neuromorphic, unconventional - and beyond

H. Jaeger, 2020, ArXiv.

Links between multiplicity automata, observable operator models and predictive state representations: a unified learning framework

Herbert Jaeger, Michael R. Thon, H. Jaeger, 2015, J. Mach. Learn. Res..

An Introduction to Dynamic Concept Systems

Herbert Jaeger, H. Jaeger, 1991, PDK.

Adaptive Nonlinear System Identification with Echo State Networks

Herbert Jaeger, H. Jaeger, 2002, NIPS.

Echo State Property Linked to an Input: Exploring a Fundamental Characteristic of Recurrent Neural Networks

Herbert Jaeger, Manjunath Gandhi, H. Jaeger, 2013, Neural Computation.

Overview of Reservoir Recipes

Herbert Jaeger, Mantas Lukoševičius, H. Jaeger, 2007 .

Frequency modulation of large oscillatory neural networks

Benjamin Schrauwen, Herbert Jaeger, Francis Wyffels, 2014, Biological Cybernetics.

Theory of Input Driven Dynamical Systems

Peter Tiño, Herbert Jaeger, Manjunath Gandhi, 2012, ESANN.

Minimal Energy Control of an ESN Pattern Generator

Herbert Jaeger, Jiwen Li, H. Jaeger, 2011 .

Reservoir riddles: suggestions for echo state network research

H. Jaeger, H. Jaeger, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Overcoming Catastrophic Interference by Conceptors pdf

Xu He, Herbert Jaeger, H. Jaeger, 2017, ArXiv.

From Continuous Dynamics to Symbols

Herbert Jaeger, H. Jaeger, 1999 .

Herbert Jaeger , Communication Systems and Saving Energy in Wireless Harnessing Nonlinearity : Predicting Chaotic

H. Jaeger, H. Haas, 2008 .

A tutorial on training recurrent neural networks , covering BPPT , RTRL , EKF and the " echo state network " approach - Semantic Scholar

Herbert Jaeger, H. Jaeger, 2005 .

Norm-Observable Operator Models

Herbert Jaeger, MingJie Zhao, H. Jaeger, 2010, Neural Computation.

Conceptors: an easy introduction pdf

Herbert Jaeger, H. Jaeger, 2014, ArXiv.

Learning to Ground Fact Symbols in Behavior-Based Robots

Joachim Hertzberg, Herbert Jaeger, Frank Schönherr, 2002, ECAI.

Reservoir Transfer on Analog Neuromorphic Hardware

Tianlin Liu, Xu He, Herbert Jaeger, 2019, 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER).

Optimization and applications of echo state networks with leaky- integrator neurons

D. Popovici, H. Jaeger, M. Lukoševičius, 2007, Neural Networks.

Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes

Herbert Jaeger, Gilles Wainrib, Mathieu Galtier, 2014, Neural Networks.

Stepping forward through echoes of the past : forecasting with Echo State Networks

H. Jaeger, O. Kosuchinas, M. Rincón, 2007 .

Toward a formal theory for computing machines made out of whatever physics offers

H. Jaeger, B. Noheda, W. G. Wiel, 2023, Nature Communications.

Self-organization of feature detectors in time sequences (SOFT)-a neural network approach to multidimensional signal analysis

A. Wismuller, H. Jaeger, H. Ritter, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Characterization of Ergodic Hidden Markov Sources

Alexander Schönhuth, Herbert Jaeger, H. Jaeger, 2009, IEEE Transactions on Information Theory.

Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes

G. Wainrib, H. Jaeger, M. Galtier, 2014, Neural Networks.

Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

H. Jaeger, H. Haas, 2004, Science.

Eu Fp7 Amarsi Adaptive Modular Architectures for Rich Motor Skills Technical Report on Describing the Archetype Architectures from Annex 1

H. Jaeger, Jacobs, 2011 .

Experiences Using the Dynamical System Paradigm for Programming RoboCup Robots

Herbert Jaeger, Hans-Ulrich Kobialka, H. Jaeger, 2003 .

The Dual Dynamics Design Scheme for Behavior based Robots A Tutorial

Herbert Jaeger, H. Jaeger, 1996 .