Christian K. Machens

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 12

Top Topics

Unsupervised Learning

Spiking Neurons

Nonlinear Dynamics

Top Venues

PLoS Comput. Biol.

Publications

Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin, Christian K. Machens, Michael B. Orger, Adrien Jouary
Learning interpretable control inputs and dynamics underlying animal locomotion. ICLR (2024)
William F. Podlaski, Christian K. Machens
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks. Neural Comput. 36 (5) (2024)
William F. Podlaski, Christian K. Machens
Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks. CoRR (2023)
Evren Gokcen, Anna Jasper, Alison Xu, Adam Kohn, Christian K. Machens, Byron M. Yu
Uncovering motifs of concurrent signaling across multiple neuronal populations. NeurIPS (2023)
Evren Gokcen, Anna Jasper, João D. Semedo, Amin Zandvakili, Adam Kohn, Christian K. Machens, Byron M. Yu
Disentangling the flow of signals between populations of neurons. Nat. Comput. Sci. 2 (8) (2022)
William F. Podlaski, Christian K. Machens
Biological credit assignment through dynamic inversion of feedforward networks. CoRR (2020)
Allan Mancoo, Sander W. Keemink, Christian K. Machens
Understanding spiking networks through convex optimization. NeurIPS (2020)
Wieland Brendel, Ralph Bourdoukan, Pietro Vertechi, Christian K. Machens, Sophie Denève
Learning to represent signals spike by spike. PLoS Comput. Biol. 16 (3) (2020)
William F. Podlaski, Christian K. Machens
Biological credit assignment through dynamic inversion of feedforward networks. NeurIPS (2020)
Severin Berger, Christian K. Machens
Compact task representations as a normative model for higher-order brain activity. NeurIPS (2020)
Alireza Alemi, Christian K. Machens, Sophie Denève, Jean-Jacques E. Slotine
Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules. AAAI (2018)
Adrien Wohrer, Christian K. Machens
On the Number of Neurons and Time Scale of Integration Underlying the Formation of Percepts in the Brain. PLoS Comput. Biol. 11 (3) (2015)
João D. Semedo, Amin Zandvakili, Adam Kohn, Christian K. Machens, Byron M. Yu
Extracting Latent Structure From Multiple Interacting Neural Populations. NIPS (2014)
Pietro Vertechi, Wieland Brendel, Christian K. Machens
Unsupervised learning of an efficient short-term memory network. NIPS (2014)
Martin Boerlin, Christian K. Machens, Sophie Denève
Predictive Coding of Dynamical Variables in Balanced Spiking Networks. PLoS Comput. Biol. 9 (11) (2013)
David G. T. Barrett, Sophie Denève, Christian K. Machens
Firing rate predictions in optimal balanced networks. NIPS (2013)
Ralph Bourdoukan, David G. T. Barrett, Christian K. Machens, Sophie Denève
Learning optimal spike-based representations. NIPS (2012)
Wieland Brendel, Ranulfo Romo, Christian K. Machens
Demixed Principal Component Analysis. NIPS (2011)
Christian K. Machens
Demixing Population Activity in Higher Cortical Areas. Frontiers Comput. Neurosci. 4 (2010)
Adrien Wohrer, Ranulfo Romo, Christian K. Machens
Linear readout from a neural population with partial correlation data. NIPS (2010)
Christian K. Machens, Carlos D. Brody
Design of Continuous Attractor Networks with Monotonic Tuning Using a Symmetry Principle. Neural Comput. 20 (2) (2008)
Fredrik Edin, Christian K. Machens, Hartmut Schütze, Andreas V. M. Herz
Searching for Optimal Sensory Signals: Iterative Stimulus Reconstruction in Closed-Loop Experiments. J. Comput. Neurosci. 17 (1) (2004)
Christian K. Machens, Michael Wehr, Anthony M. Zador
Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex. NIPS (2002)
Susanne Schreiber, Christian K. Machens, Andreas V. M. Herz, Simon B. Laughlin
Energy-Efficient Coding with Discrete Stochastic Events. Neural Comput. 14 (6) (2002)
Christian K. Machens, P. Prinz, Martin B. Stemmler, Bernhard Ronacher, Andreas V. M. Herz
Discrimination of behaviorally relevant signals by auditory receptor neurons. Neurocomputing (2001)