Leo-Simpson / c-lasso
c-lasso: a Python package for constrained sparse regression and classification
☆30Updated 3 years ago
Related projects: ⓘ
- A Python package for General Graphical Lasso computation☆30Updated 8 months ago
- Initialization is critical for preserving global data structure in both t-SNE and UMAP☆21Updated 3 years ago
- Perform inference on algorithm-agnostic variable importance in Python☆20Updated 2 years ago
- PyTorch implementation of the paper "Neural Decomposition: Functional ANOVA with Variational Autoencoders"☆23Updated 4 years ago
- Probabilistic contrastive principal component analysis (PCPCA)☆24Updated 2 years ago
- Fast Laplacian Eigenmaps: lightweight multicore LE for non-linear dimensional reduction with minimal memory usage. Outperforms sklearn's …☆22Updated 2 years ago
- Fast computation of diffusion maps and geometric harmonics in Python. Moved to https://git.sr.ht/~jmbr/diffusion-maps☆42Updated 3 years ago
- k-Nearest Neighbor Information Estimator☆24Updated 5 years ago
- Software for selective inference☆15Updated last year
- A library for bayesian variable selection☆27Updated 2 months ago
- Attraction-Repulsion Spectrum in Neighbor Embeddings☆30Updated last year
- Path algorithm for generalized lasso problems☆32Updated last year
- Python code for intrinsic dimension estimation of generic datasets☆20Updated 5 years ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆23Updated 5 years ago
- Sparse Principal Component Analysis (SPCA) using Variable Projection☆61Updated 6 years ago
- Code for the paper "End-to-end training of deep probabilistic CCA on paired biomedical observations".☆25Updated 3 years ago
- Use LSTM neural network for 1D distributional data prediction☆22Updated last year
- Approximate knockoffs and model-free variable selection.☆49Updated 2 years ago
- Sparse-input neural networks☆22Updated last year
- ☆13Updated 2 months ago
- Knockoffs for controlled variable selection☆32Updated last year
- Random feature latent variable models in Python☆21Updated last year
- Gaussian-Processes Surrogate Optimisation in python☆19Updated 3 years ago
- generalized principal component analysis (GLM-PCA) implemented in python☆56Updated 3 years ago
- R package to perform statistical inference in generative models using the Wasserstein distance (requires CGAL)☆24Updated 4 years ago
- A multi-algorithm Python framework for regularized regression☆12Updated 10 months ago
- L1-regularized least squares with PyTorch☆63Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 7 months ago
- Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning☆14Updated 3 years ago
- A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-conve…☆53Updated last year