andim / projgradLinks
Projected gradient optimization in python
☆16Updated 7 years ago
Alternatives and similar repositories for projgrad
Users that are interested in projgrad are comparing it to the libraries listed below
Sorting:
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty i…☆267Updated 2 months ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- A Python package for building Bayesian models with TensorFlow or PyTorch☆176Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- A Spatio-temporal point process simulator.☆48Updated 2 years ago
- LaTeX style file for the Journal of Machine Learning Research☆159Updated last year
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- Python-based Derivative-Free Optimization with Bound Constraints☆91Updated last week
- Gaussian process modelling in Python☆225Updated 11 months ago
- Literature and light wrappers for gaussian process models.☆47Updated 4 years ago
- Forecasting with PyTorch☆55Updated last week
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated last year
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 4 years ago
- A curated list of resources for learning Gaussian Processes☆40Updated 4 years ago
- Dynamic causal Bayesian optimisation☆40Updated 2 years ago
- Multi-Output Gaussian Process Toolkit☆184Updated 6 months ago
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆80Updated 2 years ago
- Bayesian Optimization of Combinatorial Structures☆99Updated 6 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Time series forecasting with PyTorch☆85Updated last week
- Simple implementation of the CGP-UCB algorithm.☆38Updated 6 years ago
- ☆123Updated last year
- PyHopper is a hyperparameter optimizer, made specifically for high-dimensional problems arising in machine learning research.☆85Updated last year
- ☆155Updated 3 years ago
- Multi-task Gaussian Process☆45Updated 10 years ago
- Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.☆235Updated 6 months ago
- Bayesian Learning and Neural Networks (jupyter book sources)☆57Updated 2 years ago