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Jakob H. Macke

31 papers · 2006–2025 · 3 conferences · across top CS/AI conferences

Achievements

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+14 more ↓ 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (15) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (7) 🐣 Hot Topic Early Bird
πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (15) 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (23) 🀝 Dynamic Duo (11) πŸ† Keyword Champion πŸ’Ž Century Club (31) πŸ—ƒοΈ Keyword Collector (67) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (5) ❓ The Questioner πŸš€ Conference Pioneer πŸ“ˆ Trend Setter

Conferences

NIPS (23) ICLR (4) ICML (4)

Papers

Compositional simulation-based inference for time series ICLR 2025 Inferring stochastic low-rank recurrent neural networks from neural data NIPS 2024 All-in-one simulation-based inference ICML 2024 Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation NIPS 2024 Simultaneous identification of models and parameters of scientific simulators ICML 2024 Latent Diffusion for Neural Spiking Data NIPS 2024 Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations ICML 2024 Flow Matching for Scalable Simulation-Based Inference NIPS 2023 Adversarial robustness of amortized Bayesian inference ICML 2023 Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation NIPS 2023 Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference NIPS 2023 Efficient identification of informative features in simulation-based inference NIPS 2022 Truncated proposals for scalable and hassle-free simulation-based inference NIPS 2022 GATSBI: Generative Adversarial Training for Simulation-Based Inference ICLR 2022 Group equivariant neural posterior estimation ICLR 2022 Variational methods for simulation-based inference ICLR 2022 Intrinsic dimension of data representations in deep neural networks NIPS 2019 Flexible statistical inference for mechanistic models of neural dynamics NIPS 2017 Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations NIPS 2017 Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NIPS 2017 Unlocking neural population non-stationarities using hierarchical dynamics models NIPS 2015 A Bayesian model for identifying hierarchically organised states in neural population activity NIPS 2014 Low-dimensional models of neural population activity in sensory cortical circuits NIPS 2014 Inferring neural population dynamics from multiple partial recordings of the same neural circuit NIPS 2013 Spectral learning of linear dynamics from generalised-linear observations with application to neural population data NIPS 2012 Empirical models of spiking in neural populations NIPS 2011 How biased are maximum entropy models? NIPS 2011 Bayesian estimation of orientation preference maps NIPS 2009 Receptive Fields without Spike-Triggering NIPS 2007 Bayesian Inference for Spiking Neuron Models with a Sparsity Prior NIPS 2007 Inducing Metric Violations in Human Similarity Judgements NIPS 2006