neurostatslab / wishart-process
Estimating Noise Correlations in Neural Populations with Wishart Processes
☆8Updated 11 months ago
Alternatives and similar repositories for wishart-process:
Users that are interested in wishart-process are comparing it to the libraries listed below
- ☆23Updated last year
- Gaussian Process Factor Analysis with Dynamical Structure☆16Updated 4 years ago
- Dynamical Components Analysis☆32Updated last year
- Demixed Shared Component Analysis☆13Updated 4 years ago
- Code for Galgali et al, 2023☆13Updated 2 years ago
- PyTorch Lightning utilities that make it easier to train and evaluate deep models for the Neural Latents Benchmark.☆8Updated 2 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆58Updated 10 months ago
- A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆21Updated last year
- Pytorch implementation of lfads, and hierarchical extension☆26Updated 3 years ago
- Fitting low-rank RNNs to neural trajectories (LINT method).☆16Updated last month
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆73Updated 4 years ago
- Pytorch implementation of LFADS for demo at CAN workshop☆19Updated 5 years ago
- ☆19Updated 2 months ago
- ☆48Updated 3 years ago
- ☆38Updated last year
- Exercises and examples for the latent dynamics workshop☆17Updated last year
- NeuroTask: A Benchmark Dataset for Multi-Task Neural Analysis☆11Updated last week
- A generalised Gaussian process method for learning vector fields over non-Euclidean domains. Particularly useful for EEG data analysis an…☆23Updated 5 months ago
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆67Updated last year
- 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
- Poisson Identifiable VAE (pi-VAE)☆51Updated 3 years ago
- Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.☆39Updated 2 years ago
- The framework for inferring Langevin dynamics from spike data☆32Updated 2 months ago
- Code for "Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations"☆9Updated 3 years ago
- ☆20Updated last year
- Convert biological neuronal networks to artificial recurrent neuronal networks☆21Updated 2 years ago
- Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics☆10Updated last year
- Recurrent state-space models for decision making☆30Updated 2 years ago
- ☆70Updated 2 years ago
- latent manifold tuning model / P-GPLVM☆12Updated 5 years ago