christophmark / bayesianfridgeLinks
Sequential Monte Carlo sampler for PyMC2 models.
☆13Updated 7 years ago
Alternatives and similar repositories for bayesianfridge
Users that are interested in bayesianfridge are comparing it to the libraries listed below
Sorting:
- This implementation of DeePyMoD is no longer maintained! We switched to a PyTorch based implementation: https://github.com/PhIMaL/DeePyM…☆24Updated 5 years ago
- ☆10Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Implementation of the Orthogonal Instantaneous Linear Mixing Model☆9Updated 2 years ago
- Layered distributions using FLAX/JAX☆10Updated 4 years ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 2 years ago
- Learning with operator-valued kernels☆22Updated 2 years ago
- ☆26Updated 5 years ago
- LaTeX source code for the slides☆23Updated 4 years ago
- Functional matrix factorization via Bayesian tensor filtering☆13Updated 2 years ago
- ☆30Updated 2 years ago
- Application of principal component analysis capturing non-linearity in the data using kernel approach☆8Updated 6 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 4 years ago
- Compute set of important operations for HCTSA code☆26Updated 5 years ago
- Auxiliary variable Markov chain Monte Carlo methods☆10Updated 7 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing…☆12Updated 5 years ago
- The Union of Intersections Framework in Python☆14Updated this week
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆16Updated 6 years ago
- Code for the paper Recurrent Machines for Likelihood-Free Inference☆15Updated 6 years ago
- Recyclable Gaussian Processes☆11Updated 2 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆28Updated 4 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆28Updated 4 years ago
- ☆16Updated 8 years ago
- Quasi-Newton Algorithm for Stochastic Optimization☆10Updated 3 years ago
- Kalman Optimization for Value Approximation☆11Updated 5 years ago
- A thorough, straightforward, un-intimidating introduction to Gaussian processes in NumPy.☆16Updated 7 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 5 years ago
- Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)☆18Updated 7 years ago
- Project on Causal Machine learning CS 7290☆16Updated 5 years ago