Mathematical Modeling seminars
April 2024
Recorded
Biologically motivated learning dynamics: parallel architectures and nonlinear Hebbian plasticity.
Michael Buice· Allen InstituteVideo · 31 min
November 2022
Recorded
The role of population structure in computations through neural dynamics
Alexis Dubreuil· French National Centre for Scientific Research (CNRS), BordeauxVideo · 46 min
September 2022
Recorded
Learning static and dynamic mappings with local self-supervised plasticity
Pantelis Vafeidis· California Institute of TechnologyVideo
June 2022
Recorded
Canonical neural networks perform active inference
Takuya Isomura· RIKEN CBSVideo · 1 h 13 min
Recorded
Trading Off Performance and Energy in Spiking Networks
Sander Keemink· Donders Institute for Brain, Cognition and BehaviourVideo · 31 min
Recorded
Heterogeneity and non-random connectivity in reservoir computing
Abigail Morrison· Jülich Research Centre & RWTH Aachen University, GermanyVideo · 52 min
March 2022
Recorded
Parametric control of flexible timing through low-dimensional neural manifolds
Manuel Beiran· Center for Theoretical Neuroscience, Columbia University & Rajan lab, Icahn School of Medicine at Mount SinaiVideo
January 2022
Recorded
December 2021
Recorded
NMC4 Short Talk: Predictive coding is a consequence of energy efficiency in recurrent neural networks
Abdullahi Ali· Donders Institute for BrainVideo page
Recorded
NMC4 Keynote: Latent variable modeling of neural population dynamics - where do we go from here?
Chethan Pandarinath· Georgia Tech & Emory UniversityVideo page
November 2021
Thu, Nov 18 · 16:00 UTC · Online
When and (maybe) why do high-dimensional neural networks produce low-dimensional dynamics?
Eric Shea-Brown· Department of Applied Mathematics, University of Washington
Recorded
Event-based Backpropagation for Exact Gradients in Spiking Neural Networks
Christian Pehle· Heidelberg UniversityVideo · 23 min
September 2021
Recorded
Credit Assignment in Neural Networks through Deep Feedback Control
Alexander Meulemans· Institute of Neuroinformatics, University of Zürich and ETH ZürichVideo · 55 min
May 2021
Recorded
A theory for Hebbian learning in recurrent E-I networks
Samuel Eckmann· Gjorgjieva lab, Max Planck Institute for Brain Research, Frankfurt, GermanyVideo
April 2021
Recorded
Recurrent network dynamics lead to interference in sequential learning
Friedrich Schuessler· Barak lab, Technion, Haifa, IsraelVideo
March 2021
Recorded
Untangling brain wide current flow using neural network models
Kanaka Rajan· Mount SinaiVideo · 1 h 16 min
December 2020
Recorded
Linking dimensionality to computation in neural networks
Stefano Recanatesi· University of WashingtonVideo · 54 min
September 2020
Recorded
Using noise to probe recurrent neural network structure and prune synapses
Rishidev Chaudhuri· University of California, DavisVideo · 54 min
Wed, Sep 16 · 03:00 UTC · Online
Theory of gating in recurrent neural networks
Kamesh Krishnamurthy· Princeton University
June 2020
Recorded
Disentangling the roles of dimensionality and cell categories in neural computations
Srdjan Ostojic· École Normale SupérieureVideo
End of results.