adrian-valente / lowrank_inferenceLinks
Fitting low-rank RNNs to neural trajectories (LINT method).
☆16Updated 2 months ago
Alternatives and similar repositories for lowrank_inference
Users that are interested in lowrank_inference are comparing it to the libraries listed below
Sorting:
- A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA☆35Updated last year
- Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portr…☆72Updated 3 months ago
- ☆52Updated 2 years ago
- Library to perform Slice Tensor Component Analysis (sliceTCA)☆52Updated 2 months ago
- Supplementary code for the paper "Linking connectivity, dynamics and computations in low-rank recurrent neural networks" by F. Mastrogius…☆34Updated 6 years ago
- Code for Galgali et al, 2023☆13Updated 2 years ago
- Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)☆53Updated 4 years ago
- State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data☆49Updated 8 months ago
- A dimensionality reduction framework for characterizing the multi-dimensional, concurrent flow of signals across multiple neuronal popula…☆16Updated 2 months ago
- A PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆100Updated 4 months ago
- Python tools for participating in Neural Latents Benchmark '21☆61Updated 10 months ago
- Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals☆20Updated last month
- GLMCC: The generalized linear model for spike cross-correlation (Kobayashi et al., Nature Communications, 2019)☆35Updated 2 years ago
- A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆21Updated last year
- A dimensionality reduction framework for disentangling the flow of signals between populations of neurons☆31Updated last month
- NEural MOdelS, a statistical modeling framework for neuroscience.☆98Updated this week
- Dynamical Similarity Analysis code accompanying the paper "Beyond Geometry: comparing the temporal structure of computation in neural cir…☆59Updated 3 weeks ago
- Sparse Component Analysis: An unsupervised method for recovering interpretable latent factors☆28Updated 3 months ago
- ☆22Updated 2 weeks ago
- Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.☆38Updated 2 years ago
- Preferential Subspace Identification Algorithm☆52Updated last week
- ☆20Updated 3 years ago
- A course given at the 2017 Canadian Neuroscience meeting, Neural Signal Analysis Satellite.☆14Updated 7 years ago
- NeuroTask: A Benchmark Dataset for Multi-Task Neural Analysis☆12Updated last month
- ☆23Updated last year
- Code to reproduce figures for "Mice alternate between discrete strategies during perceptual decision-making" from Ashwood, Roy, Stone, IB…☆48Updated last year
- ☆30Updated last year
- Code for "Cortical areas interact through a communication subspace", Semedo et al. (Neuron, 2019)☆46Updated 5 years ago
- Fitting and analysis of trial-based neural spike responses with Generalized Linear Model (GLM).☆70Updated 5 years ago
- A repository of neural manifold techniques described and compared in "Neural manifold analysis of brain circuit dynamics in health and di…☆25Updated last year