Daniel Durstewitz

Orcid: 0000-0002-9340-3786

According to our database¹, Daniel Durstewitz authored at least 29 papers between 1996 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2024

Visualization of Discontinuous Vector Field Topology.

[BibT_eX]

[DOI]

Egzon Miftari

Daniel Durstewitz

Filip Sadlo

IEEE Trans. Vis. Comput. Graph., January, 2024

Out-of-Domain Generalization in Dynamical Systems Reconstruction.

[BibT_eX]

[DOI]

Niclas Alexander Göring

CoRR, 2024

2023

Bifurcations and loss jumps in RNN training.

[BibT_eX]

[DOI]

Lukas Eisenmann

Zahra Monfared

Niclas Alexander Göring

Daniel Durstewitz

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalized Teacher Forcing for Learning Chaotic Dynamics.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems.

[BibT_eX]

[DOI]

Manuel Brenner

Georgia Koppe

Daniel Durstewitz

CoRR, 2022

On the difficulty of learning chaotic dynamics with RNNs.

[BibT_eX]

[DOI]

Jonas M. Mikhaeil

Zahra Monfared

Daniel Durstewitz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Identifying nonlinear dynamical systems from multi-modal time series data.

[BibT_eX]

[DOI]

CoRR, 2021

How to train RNNs on chaotic data?

[BibT_eX]

[DOI]

Zahra Monfared

Jonas M. Mikhaeil

Daniel Durstewitz

CoRR, 2021

Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time.

[BibT_eX]

[DOI]

Zahra Monfared

Daniel Durstewitz

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2019

Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization.

[BibT_eX]

[DOI]

CoRR, 2019

LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos.

[BibT_eX]

[DOI]

Shehabeldin Elzoheiry

Oliver Kann

Daniel Durstewitz

Fred A. Hamprecht

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Detecting Multiple Change Points Using Adaptive Regression Splines With Application to Neural Recordings.

[BibT_eX]

[DOI]

Hazem Toutounji

Daniel Durstewitz

Frontiers Neuroinformatics, 2018

2017

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

[BibT_eX]

[DOI]

Daniel Durstewitz

PLoS Comput. Biol., 2017

Sparse convolutional coding for neuronal assembly detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity.

[BibT_eX]

[DOI]

Joachim Hass

Loreen Hertäg

Daniel Durstewitz

PLoS Comput. Biol., 2016

Cell assemblies at multiple time scales with arbitrary lag distributions.

[BibT_eX]

[DOI]

Eleonora Russo

Daniel Durstewitz

CoRR, 2016

A State Space Approach for Piecewise-Linear Recurrent Neural Networks for Reconstructing Nonlinear Dynamics from Neural Measurements.

[BibT_eX]

[DOI]

Daniel Durstewitz

CoRR, 2016

2014

Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise.

[BibT_eX]

[DOI]

Loreen Hertäg

Daniel Durstewitz

Nicolas Brunel

Frontiers Comput. Neurosci., 2014

2012

An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data.

[BibT_eX]

[DOI]

Frontiers Comput. Neurosci., 2012

2011

Models of dopaminergic modulation.

[BibT_eX]

[DOI]

Joachim Hass

Daniel Durstewitz

Scholarpedia, 2011

Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making.

[BibT_eX]

[DOI]

Emili Balaguer-Ballester

Christopher C. Lapish

Jeremy K. Seamans

Daniel Durstewitz

PLoS Comput. Biol., 2011

2009

Implications of synaptic biophysics for recurrent network dynamics and active memory.

[BibT_eX]

[DOI]

Daniel Durstewitz

Neural Networks, 2009

2008

Dopamine modulation.

[BibT_eX]

[DOI]

Jeremy K. Seamans

Daniel Durstewitz

Scholarpedia, 2008

2002

The computational role of dopamine D1 receptors in working memory.

[BibT_eX]

[DOI]

Daniel Durstewitz

Jeremy K. Seamans

Neural Networks, 2002

1996

The Possible Function of Dopamine in Associative Learning: A Computational Model.

[BibT_eX]

[DOI]

Daniel Durstewitz

Onur Güntürkün

Proceedings of the Artificial Neural Networks, 1996

Daniel Durstewitz

Timeline

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