davindicode / cosyne-2023-generative-modelsLinks
Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.
☆39Updated 2 years ago
Alternatives and similar repositories for cosyne-2023-generative-models
Users that are interested in cosyne-2023-generative-models are comparing it to the libraries listed below
Sorting:
- Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)☆54Updated 4 years ago
- Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portr…☆87Updated 2 months ago
- Library to perform Slice Tensor Component Analysis (sliceTCA)☆54Updated 7 months ago
- Dynamical Similarity Analysis code accompanying the paper "Beyond Geometry: comparing the temporal structure of computation in neural cir…☆66Updated last month
- ☆59Updated 3 years ago
- Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-i…☆84Updated last month
- Supplementary code for the paper "Linking connectivity, dynamics and computations in low-rank recurrent neural networks" by F. Mastrogius…☆35Updated 7 years ago
- Some methods for comparing network representations in deep learning and neuroscience.☆140Updated last year
- NEural MOdelS, a statistical modeling framework for neuroscience.☆106Updated this week
- ☆81Updated 3 years ago
- A repository of neural manifold techniques described and compared in "Neural manifold analysis of brain circuit dynamics in health and di…☆29Updated 2 years ago
- A Guide to Reconstructing Dynamical Systems from Neural Measurements Using Recurrent Neural Networks☆38Updated last year
- A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA☆39Updated last year
- Python tools for participating in Neural Latents Benchmark '21☆63Updated last year
- Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals☆24Updated 5 months ago
- ☆30Updated 3 years ago
- Sparse Component Analysis: An unsupervised method for recovering interpretable latent factors☆28Updated 7 months ago
- A PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆114Updated 8 months ago
- STATS320: Statistical Methods for Neural Data Analysis☆198Updated 4 months ago
- State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data☆49Updated last week
- jPCA for Neural Data Analysis in Python☆50Updated 2 years ago
- This reading list is centered around the practical application of linear dynamical systems models to predict neural data☆40Updated 3 years ago
- Preferential Subspace Identification Algorithm☆54Updated 4 months ago
- Code for Galgali et al, 2023☆13Updated 2 years ago
- ☆54Updated 3 months ago
- OpenScope databook: a collaborative, versioned, data-centric collection of foundational analyses for reproducible systems neuroscience 🐁…☆73Updated 2 months ago
- A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆22Updated 2 years ago
- A dimensionality reduction framework for disentangling the flow of signals between populations of neurons☆33Updated last month
- Code to accompany the textbook "Modeling Neural Circuits Made Simple"☆158Updated last year
- Code for "Cortical areas interact through a communication subspace", Semedo et al. (Neuron, 2019)☆47Updated 6 years ago