mackelab / delfi
Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
☆73Updated 4 years ago
Alternatives and similar repositories for delfi:
Users that are interested in delfi are comparing it to the libraries listed below
- Sequential Neural Likelihood☆39Updated 5 years ago
- Black box variational inference for state space models☆1Updated 8 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 9 months ago
- Tree-structured recurrent switching linear dynamical systems☆36Updated 4 years ago
- Conditional density estimation with neural networks☆30Updated 2 months ago
- A Python 3 toolbox for neural receptive field estimation using splines and Gaussian priors.☆24Updated 7 months ago
- Dynamical Components Analysis☆32Updated last year
- ☆23Updated last year
- Dimensionality reduction of spikes trains☆49Updated 3 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆62Updated 2 months ago
- SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory☆22Updated last year
- Recurrent Switching Linear Dynamical Systems☆106Updated last year
- A Python toolkit for (simulation-based) inference and the mechanization of science.☆53Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified …☆18Updated 7 years ago
- Recurrent state-space models for decision making☆30Updated 2 years ago
- Code for fitting neural spike trains with nonparametric hidden Markov and semi-Markov models built upon mattjj's PyHSMM framework.☆14Updated 6 years ago
- Automated dynamical systems inference☆38Updated last year
- ☆94Updated 6 years ago
- ABCpy package☆113Updated 10 months ago
- Simulation-based inference benchmark☆96Updated last month
- Interpretable neural spike train models with fully-Bayesian inference algorithms☆47Updated 6 years ago
- Data and example scripts used in the paper `Inferring hidden structure in multilayered neural circuits`☆14Updated 3 years ago
- Preconditioned ICA for Real Data☆108Updated 4 months ago
- local non-uniformity correction for mutual information estimation☆69Updated 3 years ago
- Pytorch implementation of lfads, and hierarchical extension☆26Updated 3 years ago
- Combination of transformers and diffusion models for flexible all-in-one simulation-based inference☆60Updated 9 months ago
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆64Updated last year
- Seminar on Advanced Topics in Theoretical Neuroscience - Columbia University 2020☆10Updated 4 years ago
- My PhD Thesis☆22Updated 8 years ago