takuyaisomura / predpca
Predictive principal component analysis (PredPCA)
☆19Updated 3 years ago
Alternatives and similar repositories for predpca:
Users that are interested in predpca are comparing it to the libraries listed below
- Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"☆23Updated 4 years ago
- Extended Dynamic Mode Decomposition for system identification from time series data (with dictionary learning, control and streaming opti…☆30Updated 7 months ago
- Multi-task regression in Python☆25Updated 4 years ago
- General framework for Bayesian inversion of continuous hierarchical models☆10Updated 3 years ago
- The framework for inferring Langevin dynamics from spike data☆32Updated 3 months ago
- resources related to papers☆13Updated 10 months ago
- The Union of Intersections Framework in Python☆14Updated last week
- ☆20Updated 2 months ago
- ☆14Updated last year
- A generalised Gaussian process method for learning vector fields over non-Euclidean domains. Particularly useful for EEG data analysis an…☆23Updated 6 months ago
- Perform inference on algorithm-agnostic variable importance in Python☆20Updated 2 years ago
- Hopefully, a compact and general-purpose Python package for Multiperturbation Shapley value Analysis (MSA).☆18Updated 10 months ago
- Optimisation on Diffeomorphisms☆12Updated 2 months ago
- Official code for UnICORNN (ICML 2021)☆27Updated 3 years ago
- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data (Pytorch)☆17Updated 2 years ago
- ☆29Updated 6 years ago
- PyTorch implementation of Robust Non-negative Tensor Factorization appearing in N. Dey, et al., "Robust Non-negative Tensor Factorization…☆20Updated last year
- Energy Landscape Analysis Toolbox (ELAT) for MATLAB☆21Updated 5 months ago
- ☆10Updated 4 years ago
- ☆17Updated 6 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆118Updated last year
- An sklearn style implementation of the Relevance Vector Machine (RVM).☆24Updated 5 years ago
- PyTorch implementation of the Covariate-GPLVM☆26Updated 5 years ago
- Estimating Noise Correlations in Neural Populations with Wishart Processes☆8Updated 11 months ago
- ☆11Updated 6 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- Gaussian process regression + automatical model selection for logitudinal -omics data☆21Updated 4 years ago
- Official implementation of GPX: Gaussian Process Regression with Interpretable Sample-wise Feature Weights (published on TNNLS)☆17Updated 3 years ago
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆59Updated 10 months ago
- Neural Optimal Feedback Control☆11Updated 3 years ago