lhnguyen102 / cuTAGILinks
CUDA implementation of Tractable Approximate Gaussian Inference
☆41Updated this week
Alternatives and similar repositories for cuTAGI
Users that are interested in cuTAGI are comparing it to the libraries listed below
Sorting:
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- Materials of the Nordic Probabilistic AI School 2022.☆180Updated 2 years ago
- Hierarchical Associative Memory User Experience☆103Updated last month
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆308Updated 2 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- ☆312Updated 5 months ago
- Neat Bayesian machine learning examples☆58Updated 2 months ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆137Updated 2 months ago
- A Python package of computer vision models for the Equinox ecosystem.☆108Updated last year
- TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch☆80Updated last year
- Official Implementation of the ICML 2023 paper: "Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally …☆73Updated 2 years ago
- ☆152Updated 2 years ago
- Running Jax in PyTorch Lightning☆113Updated 8 months ago
- ☆191Updated 2 months ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 months ago
- Lightweight Hyperparameter Optimization 🚂☆150Updated last year
- Agustinus' very opiniated publication-ready plotting library☆69Updated 4 months ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- A Python package for generating concise, high-quality summaries of a probability distribution☆53Updated 5 months ago
- Pre-trained Gaussian processes for Bayesian optimization☆95Updated 4 months ago
- PyHopper is a hyperparameter optimizer, made specifically for high-dimensional problems arising in machine learning research.☆87Updated last year
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆225Updated last year
- Implementation of normalizing flows from 1d to Nd☆36Updated 4 years ago
- Bayesian algorithm execution (BAX)☆50Updated 4 years ago
- Our maintained PFN repository. Come here to train SOTA PFNs.☆103Updated last week
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆21Updated 4 years ago
- A temporary repository hosting a pomegranate re-write using PyTorch as the backend.☆72Updated 2 years ago