DurstewitzLab / CNS-2023

Related projects: ⓘ

• ShanechiLab / PyPSID
  Preferential Subspace Identification Algorithm
  ☆47Updated 2 weeks ago
• davindicode / cosyne-2023-generative-models
  Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.
  ☆39Updated last year
• mitchellostrow / DSA
  Dynamical Similarity Analysis code accompanying the paper "Beyond Geometry: comparing the temporal structure of computation in neural cir…
  ☆36Updated 2 months ago
• ahwillia / tensortools
  A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA
  ☆31Updated 11 months ago
• ShanechiLab / torchDFINE
  ☆26Updated 6 months ago
• ShanechiLab / PSID
  Preferential Subspace Identification Algorithm
  ☆44Updated 7 months ago
• rajanlab / CURBD
  Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)
  ☆48Updated 3 years ago
• pillowlab / GLMspiketraintutorial_python
  ☆46Updated 2 years ago
• egokcen / DLAG
  A dimensionality reduction framework for disentangling the flow of signals between populations of neurons
  ☆24Updated 2 years ago
• arthur-pe / slicetca
  Library to perform Slice Tensor Component Analysis (sliceTCA)
  ☆32Updated 4 months ago
• mh105 / somata
  State-space Oscillator Modeling And Time-series Analysis (SOMATA) is a Python library for state-space neural signal processing algorithms…
  ☆20Updated last month
• bantin / jPCA
  jPCA for Neural Data Analysis in Python
  ☆42Updated last year
• Eden-Kramer-Lab / replay_trajectory_classification
  State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data
  ☆43Updated last week
• DurstewitzLab / dendPLRNN
  ☆17Updated 5 months ago
• mackelab / smc_rnns
  Code accompanying Inferring stochastic low-rank RNNs from neural data. @matthijspals
  ☆11Updated last month
• kstach01 / CogModelingRNNsTutorial
  ☆46Updated 5 months ago
• neurallatents / nlb_workshop
  ☆17Updated 2 years ago
• snel-repo / autolfads-tf2
  A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.
  ☆19Updated last year
• zashwood / glm-hmm
  Code to reproduce figures for "Mice alternate between discrete strategies during perceptual decision-making" from Ashwood, Roy, Stone, IB…
  ☆41Updated last year
• egokcen / mDLAG
  A dimensionality reduction framework for characterizing the multi-dimensional, concurrent flow of signals across multiple neuronal popula…
  ☆10Updated 10 months ago
• irisstone / glmhmm
  code to fit GLMs, HMMs, and GLM-HMMs (aka IO-HMMs)
  ☆24Updated last month
• arsedler9 / lfads-torch
  A PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.
  ☆80Updated this week
• SaberaTalukder / Chen_Institute_DataSAI_for_Neuroscience
  ☆28Updated 2 years ago
• schultzlab / Neural_Manifolds
  A repository of neural manifold techniques described and compared in "Neural manifold analysis of brain circuit dynamics in health and di…
  ☆23Updated 11 months ago
• awillats / dynamics-in-neuro-reading-list
  This reading list is centered around the practical application of linear dynamical systems models to predict neural data
  ☆35Updated 2 years ago
• glaserlab / sca
  Sparse component analysis
  ☆24Updated 3 months ago
• snel-repo / ComputationThruDynamicsBenchmark
  ☆11Updated last month
• agosztolai / MARBLE
  Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portr…
  ☆27Updated last month
• zashwood / ssm
  Bayesian learning and inference for state space models
  ☆10Updated 2 years ago
• fmastrogiuseppe / LowRank
  Supplementary code for the paper "Linking connectivity, dynamics and computations in low-rank recurrent neural networks" by F. Mastrogius…
  ☆30Updated 6 years ago