Daniel Durstewitz

51 papers A* 13C 1Journal 35Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Computational network models for forecasting and control of mental health trajectories in digital applications. npj Digit. Medicine Janik Fechtelpeter, Christian Rauschenberg, Christian Goetzl, Selina Hiller, Eva Wierzba, Niklas Emonds, Silvia Krumm, Ulrich Reininghaus, Daniel Durstewitz, Georgia Koppe
2026	J	`jnl`	Continuous-Time Piecewise-Linear Recurrent Neural Networks. CoRR Alena Brändle, Lukas Eisenmann, Florian Götz, Daniel Durstewitz
2026	J	`jnl`	Position: Why a Dynamical Systems Perspective is Needed to Advance Time Series Modeling. CoRR Daniel Durstewitz, Christoph Jürgen Hemmer, Florian Hess, Charlotte Ricarda Doll, Lukas Eisenmann
2025	J	`jnl`	Detecting Invariant Manifolds in ReLU-Based RNNs. CoRR Lukas Eisenmann, Alena Brändle, Zahra Monfared, Daniel Durstewitz
2025	A*	`conf`	Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data. ICLR Manuel Brenner, Elias Weber, Georgia Koppe, Daniel Durstewitz
2025	J	`jnl`	True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics. CoRR Christoph Jürgen Hemmer, Daniel Durstewitz
2025	J	`jnl`	What Neuroscience Can Teach AI About Learning in Continuously Changing Environments. CoRR Daniel Durstewitz, Bruno Averbeck, Georgia Koppe
2024	A*	`conf`	A scalable generative model for dynamical system reconstruction from neuroimaging data. NeurIPS Eric Volkmann, Alena Brändle, Daniel Durstewitz, Georgia Koppe
2024	J	`jnl`	A scalable generative model for dynamical system reconstruction from neuroimaging data. CoRR Eric Volkmann, Alena Brändle, Daniel Durstewitz, Georgia Koppe
2024	A*	`conf`	Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction. NeurIPS Manuel Brenner, Christoph Jürgen Hemmer, Zahra Monfared, Daniel Durstewitz
2024	J	`jnl`	Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction. CoRR Manuel Brenner, Christoph Jürgen Hemmer, Zahra Monfared, Daniel Durstewitz
2024	A*	`conf`	Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics. ICML Manuel Brenner, Florian Hess, Georgia Koppe, Daniel Durstewitz
2024	J	`jnl`	Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data. CoRR Manuel Brenner, Elias Weber, Georgia Koppe, Daniel Durstewitz
2024	J	`jnl`	MTLComb: multi-task learning combining regression and classification tasks for joint feature selection. CoRR Han Cao, Sivanesan Rajan, Bianka Hahn, Ersoy Kocak, Daniel Durstewitz, Emanuel Schwarz, Verena Schneider-Lindner
2024	A*	`conf`	Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction. ICML Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess, Daniel Durstewitz
2024	J	`jnl`	Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction. CoRR Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess, Daniel Durstewitz
2024	A*	`conf`	Out-of-Domain Generalization in Dynamical Systems Reconstruction. ICML Niclas Alexander Göring, Florian Hess, Manuel Brenner, Zahra Monfared, Daniel Durstewitz
2024	J	`jnl`	Out-of-Domain Generalization in Dynamical Systems Reconstruction. CoRR Niclas Alexander Göring, Florian Hess, Manuel Brenner, Zahra Monfared, Daniel Durstewitz
2024	J	`jnl`	Visualization of Discontinuous Vector Field Topology. IEEE Trans. Vis. Comput. Graph. Egzon Miftari, Daniel Durstewitz, Filip Sadlo
2024	J	`jnl`	dsLassoCov: a federated machine learning approach incorporating covariate control. CoRR Han Cao, Augusto Anguita, Charline Warembourg, Xavier Escriba-Montagut, Martine Vrijheid, Juan R. González, Tim Cadman, Verena Schneider-Lindner, Daniel Durstewitz, Xavier Basagaña, Emanuel Schwarz
2023	A*	`conf`	Bifurcations and loss jumps in RNN training. NeurIPS Lukas Eisenmann, Zahra Monfared, Niclas Alexander Göring, Daniel Durstewitz
2023	J	`jnl`	Bifurcations and loss jumps in RNN training. CoRR Lukas Eisenmann, Zahra Monfared, Niclas Alexander Göring, Daniel Durstewitz
2023	A*	`conf`	Generalized Teacher Forcing for Learning Chaotic Dynamics. ICML Florian Hess, Zahra Monfared, Manuel Brenner, Daniel Durstewitz
2023	J	`jnl`	Generalized Teacher Forcing for Learning Chaotic Dynamics. CoRR Florian Hess, Zahra Monfared, Manuel Brenner, Daniel Durstewitz
2022	J	`jnl`	Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems. CoRR Manuel Brenner, Georgia Koppe, Daniel Durstewitz
2022	A*	`conf`	On the difficulty of learning chaotic dynamics with RNNs. NeurIPS Jonas M. Mikhaeil, Zahra Monfared, Daniel Durstewitz
2022	A*	`conf`	Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series. ICML Daniel Kramer, Philine Lou Bommer, Daniel Durstewitz, Carlo Tombolini, Georgia Koppe
2022	A*	`conf`	Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems. ICML Manuel Brenner, Florian Hess, Jonas M. Mikhaeil, Leonard F. Bereska, Zahra Monfared, Po-Chen Kuo, Daniel Durstewitz
2022	J	`jnl`	Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems. CoRR Manuel Brenner, Florian Hess, Jonas M. Mikhaeil, Leonard F. Bereska, Zahra Monfared, Po-Chen Kuo, Daniel Durstewitz
2021	J	`jnl`	How to train RNNs on chaotic data? CoRR Zahra Monfared, Jonas M. Mikhaeil, Daniel Durstewitz
2021	J	`jnl`	Identifying nonlinear dynamical systems from multi-modal time series data. CoRR Philine Lou Bommer, Daniel Kramer, Carlo Tombolini, Georgia Koppe, Daniel Durstewitz
2021	A*	`conf`	Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies. ICLR Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz
2020	A*	`conf`	Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time. ICML Zahra Monfared, Daniel Durstewitz
2019	J	`jnl`	Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI. CoRR Georgia Koppe, Hazem Toutounji, Peter Kirsch, Stefanie Lis, Daniel Durstewitz
2019	J	`jnl`	Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI. PLoS Comput. Biol. Georgia Koppe, Hazem Toutounji, Peter Kirsch, Stefanie Lis, Daniel Durstewitz
2019	J	`jnl`	Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization. CoRR Dominik Schmidt, Georgia Koppe, Max Beutelspacher, Daniel Durstewitz
2019	—	`conf`	LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. ICLR (Poster) Elke Kirschbaum, Manuel Haußmann, Steffen Wolf, Hannah Sonntag, Justus Schneider, Shehabeldin Elzoheiry, Oliver Kann, Daniel Durstewitz, Fred A. Hamprecht
2018	J	`jnl`	Detecting Multiple Change Points Using Adaptive Regression Splines With Application to Neural Recordings. Frontiers Neuroinformatics Hazem Toutounji, Daniel Durstewitz
2017	J	`jnl`	A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements. PLoS Comput. Biol. Daniel Durstewitz
2017	—	`conf`	Sparse convolutional coding for neuronal assembly detection. NIPS Sven Peter, Elke Kirschbaum, Martin Both, Lee Campbell, Brandon Harvey, Conor Heins, Daniel Durstewitz, Ferran Diego, Fred A. Hamprecht
2016	J	`jnl`	A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity. PLoS Comput. Biol. Joachim Hass, Loreen Hertäg, Daniel Durstewitz
2016	J	`jnl`	A State Space Approach for Piecewise-Linear Recurrent Neural Networks for Reconstructing Nonlinear Dynamics from Neural Measurements. CoRR Daniel Durstewitz
2016	J	`jnl`	Cell assemblies at multiple time scales with arbitrary lag distributions. CoRR Eleonora Russo, Daniel Durstewitz
2014	J	`jnl`	Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise. Frontiers Comput. Neurosci. Loreen Hertäg, Daniel Durstewitz, Nicolas Brunel
2012	J	`jnl`	An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data. Frontiers Comput. Neurosci. Loreen Hertäg, Joachim Hass, Tatiana Golovko, Daniel Durstewitz
2011	J	`jnl`	Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making. PLoS Comput. Biol. Emili Balaguer-Ballester, Christopher C. Lapish, Jeremy K. Seamans, Daniel Durstewitz
2011	J	`jnl`	Models of dopaminergic modulation. Scholarpedia Joachim Hass, Daniel Durstewitz
2009	J	`jnl`	Implications of synaptic biophysics for recurrent network dynamics and active memory. Neural Networks Daniel Durstewitz
2008	J	`jnl`	Dopamine modulation. Scholarpedia Jeremy K. Seamans, Daniel Durstewitz
2002	J	`jnl`	The computational role of dopamine D1 receptors in working memory. Neural Networks Daniel Durstewitz, Jeremy K. Seamans
1996	C	`conf`	The Possible Function of Dopamine in Associative Learning: A Computational Model. ICANN Daniel Durstewitz, Onur Güntürkün