akshey-kumar / BunDLe-NetLinks
Behavioural and Dynamic Learning Network (BunDLe-Net) is an algorithm to learn meaningful coarse-grained representations from time-series data. It maps high-dimensional data to low-dimensional space while preserving both dynamical and behavioural information. It has been applied, but is not limited to neuronal manifold learning.
☆14Updated 8 months ago
Alternatives and similar repositories for BunDLe-Net
Users that are interested in BunDLe-Net are comparing it to the libraries listed below
Sorting:
- Some methods for comparing network representations in deep learning and neuroscience.☆141Updated last year
- A curated collection of neuroscience tasks with a common interface.☆305Updated this week
- Dynamical Similarity Analysis code accompanying the paper "Beyond Geometry: comparing the temporal structure of computation in neural cir…☆71Updated last week
- Python tools for participating in Neural Latents Benchmark '21☆66Updated last year
- Fitting low-rank RNNs to neural trajectories (LINT method).☆18Updated 9 months ago
- A framework for evaluating models on their alignment to brain and behavioral measurements (100+ benchmarks)☆164Updated this week
- A package to train neural networks to perform various motor tasks☆72Updated 3 months ago
- A PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.☆120Updated this week
- Code base for the SENSORIUM competition.☆64Updated last year
- Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.☆160Updated this week
- Poisson Identifiable VAE (pi-VAE)☆52Updated 4 years ago
- A python package for simulating movement and spatial cell types (e.g. place cells, grid cells) in continuous environments.☆248Updated 2 months ago
- Official Implementation of POYO-1 https://poyo-brain.github.io/☆73Updated 3 months ago
- ☆81Updated 3 years ago
- Tutorial codes for modeling brains with neural nets☆236Updated 4 years ago
- Models and simulations for state space composition☆27Updated last year
- NiceWebRL is a Python library for quickly making human subject experiments that leverage machine reinforcement learning environments.☆76Updated 2 weeks ago
- ☆32Updated 2 years ago
- Figures, tables and stats for Schneider, Lee and Mathis 2022: Learnable latent embeddings for joint behavioral and neural analysis.☆20Updated 2 years ago
- Topographic Deep Artificial Neural Networks☆55Updated last month
- FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks☆104Updated last year
- ConvRNN Model Zoo: ImageNet pre-trained convolutional recurrent neural networks☆35Updated 2 years ago
- Supplementary code for the paper "Linking connectivity, dynamics and computations in low-rank recurrent neural networks" by F. Mastrogius…☆37Updated 7 years ago
- ☆86Updated 10 months ago
- Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portr…☆92Updated 4 months ago
- Python package for extracting representations from state-of-the-art computer vision models☆175Updated last month
- ☆29Updated 2 months ago
- ☆89Updated last week
- Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.☆39Updated 2 years ago
- A Guide to Reconstructing Dynamical Systems from Neural Measurements Using Recurrent Neural Networks☆41Updated last year