Jakob H. Macke | DeepAI

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Featured Co-authors

Bernhard Schölkopf
243 publications
Ari S. Morcos
25 publications
Mijung Park
23 publications
Lars Buesing
20 publications
Theofanis Karaletsos
19 publications
Christian F. Baumgartner
16 publications
Alessandro Laio
14 publications
David G. T. Barrett
11 publications
Srinivas C. Turaga
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Conor Durkan
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Stephen R. Green
7 publications

∙ 01/09/2023

Multiscale Metamorphic VAE for 3D Brain MRI Synthesis

Generative modeling of 3D brain MRIs presents difficulties in achieving ...

0 Jaivardhan Kapoor, et al. ∙

∙ 11/16/2022

Adapting to noise distribution shifts in flow-based gravitational-wave inference

Deep learning techniques for gravitational-wave parameter estimation hav...

0 Jonas Wildberger, et al. ∙

∙ 10/11/2022

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference

We combine amortized neural posterior estimation with importance samplin...

0 Maximilian Dax, et al. ∙

∙ 10/10/2022

Truncated proposals for scalable and hassle-free simulation-based inference

Simulation-based inference (SBI) solves statistical inverse problems by ...

0 Michael Deistler, et al. ∙

∙ 03/12/2022

GATSBI: Generative Adversarial Training for Simulation-Based Inference

Simulation-based inference (SBI) refers to statistical inference on stoc...

0 Poornima Ramesh, et al. ∙

∙ 03/08/2022

Variational methods for simulation-based inference

We present Sequential Neural Variational Inference (SNVI), an approach t...

13 Manuel Glöckler, et al. ∙

∙ 11/25/2021

Group equivariant neural posterior estimation

Simulation-based inference with conditional neural density estimators is...

0 Maximilian Dax, et al. ∙

∙ 06/23/2021

Real-time gravitational-wave science with neural posterior estimation

We demonstrate unprecedented accuracy for rapid gravitational-wave param...

38 Maximilian Dax, et al. ∙

∙ 01/12/2021

Benchmarking Simulation-Based Inference

Recent advances in probabilistic modelling have led to a large number of...

0 Jan-Matthis Lueckmann, et al. ∙

∙ 07/17/2020

SBI – A toolkit for simulation-based inference

Scientists and engineers employ stochastic numerical simulators to model...

0 Alvaro Tejero-Cantero, et al. ∙

∙ 10/03/2019

Inference of a mesoscopic population model from population spike trains

To understand how rich dynamics emerge in neural populations, we require...

21 Alexandre René, et al. ∙

∙ 06/27/2019

Teaching deep neural networks to localize sources in super-resolution microscopy by combining simulation-based learning and unsupervised learning

Single-molecule localization microscopy constructs super-resolution imag...

6 Artur Speiser, et al. ∙

∙ 05/29/2019

Intrinsic dimension of data representations in deep neural networks

Deep neural networks progressively transform their inputs across multipl...

0 Alessio Ansuini, et al. ∙

∙ 05/17/2019

Automatic Posterior Transformation for Likelihood-Free Inference

How can one perform Bayesian inference on stochastic simulators with int...

13 David S. Greenberg, et al. ∙

∙ 10/31/2018

Analyzing biological and artificial neural networks: challenges with opportunities for synergy?

Deep neural networks (DNNs) transform stimuli across multiple processing...

0 David G. T. Barrett, et al. ∙

∙ 05/23/2018

Likelihood-free inference with emulator networks

Approximate Bayesian Computation (ABC) provides methods for Bayesian inf...

0 Jan-Matthis Lueckmann, et al. ∙

∙ 11/06/2017

Flexible statistical inference for mechanistic models of neural dynamics

Mechanistic models of single-neuron dynamics have been extensively studi...

0 Jan-Matthis Lueckmann, et al. ∙

∙ 11/06/2017

Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations

A powerful approach for understanding neural population dynamics is to e...

0 Marcel Nonnenmacher, et al. ∙

∙ 11/06/2017

Fast amortized inference of neural activity from calcium imaging data with variational autoencoders

Calcium imaging permits optical measurement of neural activity. Since in...

0 Artur Speiser, et al. ∙

∙ 10/12/2014

Hierarchical models for neural population dynamics in the presence of non-stationarity

Neural population activity often exhibits rich variability and temporal ...

0 Mijung Park, et al. ∙