Wulfram Gerstner
Full Professor
Models spiking neural networks and biologically plausible learning rules, connecting computational neuroscience with reinforcement learning.
Wulfram Gerstner's lab at EPFL works on computational neuroscience & cognition, reinforcement learning and neuroscience & brain-computer interfaces. 22 papers since 2023, 7 at top venues, mostly NeurIPS and Neuron. 8 PhD students. 48 alumni. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 32%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 48
Papers by yearfrom the lab homepage, 2023–2026
- 4 papers2026 · T1 3 · collecting
- 5 papers2025 · T1 2
- 7 papers2024 · T1 0
- 6 papers2023 · T1 2
T1 venuesOtherVenues: NeurIPS, Neuron, ICML, PNAS
Research focuspaper titles that use each topic's words
- Computational neuroscience & cognition4 papers
- Reinforcement learning3 papers
- Neuroscience & brain-computer interfaces2 papers
- plausible0 papers
- rules0 papers
Paper list
From the lab homepage.
20264 papers
- ICML (T1)Can Local Learning Match Self-Supervised Backpropagation? (opens in a new tab)
- Neuromorph. Comput. Eng. 6:024018Emergence of overlapping assemblies in a dynamic attractor model of associative memory (opens in a new tab)
- Neuron (T1)Linking neural manifolds to circuit structure in recurrent networks (opens in a new tab)
- Neuron (T1)Representational similarity modulates neural and behavioral signatures of novelty (opens in a new tab)
20255 papers
- eLifeBiologically informed cortical models predict optogenetic perturbations (opens in a new tab)
- Neural Networks 192:107728Context selectivity with dynamic availability enables lifelong continual learning (opens in a new tab)
- Physical Review Letters 134:018401Emergent rate-based dynamics in duplicate-free populations of spiking neurons (opens in a new tab)
- NeurIPS (T1)Flat Channels to Infinity in Neural Loss Landscapes (opens in a new tab)
- PNAS (T1)Novelty as a drive of human exploration in complex stochastic environments (opens in a new tab)
20247 papers
- In: J. Graff and S. Ramirez (eds) Engrams. Adv. Neurobiol.A computational framework for memory engrams (opens in a new tab)
- Behavioral and Brain Science 47:e94Computational models of intrinsic motivation for curiosity and creativity (opens in a new tab)
- Cell Reports 43: 113618Distributed and specific encoding of sensory, motor, and decision information in the mouse neocortex during goal-directed behavior (opens in a new tab)
- Proceedings of the International Conference on Machine Learning (ICML), Vienna, Austria.Expand-and-Cluster: Parameter Recovery of Neural Networks (opens in a new tab)
- PLOS Comput. Biol. 20:e1011839Fast adaptation to rule switching using neuronal surprise (opens in a new tab)
- Nature Comm. 15:6793High-performance deep spiking neural networks with 0.3 spikes per neuron (opens in a new tab)
- PLOS Comput. Biol. 20:e1011844Learning what matters: synaptic plasticity with invariance to second-order input correlations (opens in a new tab)
20236 papers
- Neural Networks 168: 74-88An exact mapping from ReLU networks to spiking neural networks (opens in a new tab)
- Nature Comm. 14:2979Computational models of episodic-like memory in food-caching birds (opens in a new tab)
- Trends Neurosci. 46:1054-1066Curiosity-driven exploration: foundations in neuroscience and computational modeling (opens in a new tab)
- NeurIPS (T1)Should Under-parameterized Student Networks Copy or Average Teacher Weights? (opens in a new tab)
- Curr. Opinion Neurobiol. 82:102758Surprise and novelty in the brain (opens in a new tab)
- NeurIPS (T1)Trial matching: capturing variability with data-constrained spiking neural networks (opens in a new tab)
Where alumni went48 listed
Apply to EPFLFall 2027
EDIC Computer and Communication Sciences PhD
- Round
- Round 1
- Opens
- —
- GRE
- optional
- English
- TOEFL 100 / IELTS 7.0
- Fee
- none
Confirmed on the program page.
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