Jakob H. Macke

Full Professor@University of Tuebingen·德国·OpenReview

研究方向

likelihood free inference · ABC · Approximate Bayesian Computation · sensory systems · biological vision · computational vision · visual system · natural vision · computational neuroscience · neural dynamics · neural coding · connectomics · state-space models · dimensionality reduction · time-series models · linear systems

7.8

Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models

NeurIPS 2025Poster

通讯

7.5

Identifying multi-compartment Hodgkin-Huxley models with high-density extracellular voltage recordings

NeurIPS 2025Poster

三作

7.3

A data and task-constrained mechanistic model of the mouse outer retina shows robustness to contrast variations

NeurIPS 2025Poster

6.8

FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators

合作者 (20)

Ian Christopher Tanoh

1 篇

Jakob H. Macke

Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models

Identifying multi-compartment Hodgkin-Huxley models with high-density extracellular voltage recordings

A data and task-constrained mechanistic model of the mouse outer retina shows robustness to contrast variations

FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators

Compositional simulation-based inference for time series

Latent Diffusion for Neural Spiking Data

Inferring stochastic low-rank recurrent neural networks from neural data

Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation