← Authors

Wulfram Gerstner

18 papers · 2006–2024 · 2 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (2) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (18) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (21) 🌱 Topic Pioneer πŸ† Keyword Champion 🧬 Topic Evolution πŸ’Ž Century Club (18) πŸ—ƒοΈ Keyword Collector (55) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (6) πŸš€ Conference Pioneer ❓ The Questioner (2)

Conferences

NIPS (14) ICML (4)

Top co-authors

Johanni Brea (6) Guillaume Bellec (4) Berfin Simsek (3) Shuqi Wang (2) Gediminas LukΕ‘ys (2) Carmen Sandi (2) Dane S Corneil (1) Christos Sourmpis (1) Jean Ventura (1) Richard Naud (1)

Keywords

spiking neural network (6) reinforcement learning (3) cognitive modeling (2) stress effects (2) learning rate (2) meta-parameters (2) neural network (2) recurrent network (2) hebbian learning (2) generalized linear model (2) online learning (1) signal separation (1) independent component analysis (1) neural dynamics (1) state abstraction (1) spike prediction (1) variational inference (1) sample efficiency (1) genetic factors (1) motor control (1)

Papers

Expand-and-Cluster: Parameter Recovery of Neural Networks ICML 2024
Should Under-parameterized Student Networks Copy or Average Teacher Weights? NIPS 2023
Trial matching: capturing variability with data-constrained spiking neural networks NIPS 2023
Mesoscopic modeling of hidden spiking neurons NIPS 2022
Kernel Memory Networks: A Unifying Framework for Memory Modeling NIPS 2022
Local plasticity rules can learn deep representations using self-supervised contrastive predictions NIPS 2021
Fitting summary statistics of neural data with a differentiable spiking network simulator NIPS 2021
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances ICML 2021
Non-linear motor control by local learning in spiking neural networks ICML 2018
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation ICML 2018
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments NIPS 2015
From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models NIPS 2011
Variational Learning for Recurrent Spiking Networks NIPS 2011
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models NIPS 2010
Code-specific policy gradient rules for spiking neurons NIPS 2009
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning NIPS 2008
An online Hebbian learning rule that performs Independent Component Analysis NIPS 2007
Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning NIPS 2006