MArpogaus / bernstein_flow
A normalizing flow using Bernstein polynomials for conditional density estimation.
☆18Updated last month
Related projects ⓘ
Alternatives and complementary repositories for bernstein_flow
- A framework for composing Neural Processes in Python☆78Updated 5 months ago
- A Python library for vine copula models☆94Updated this week
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆28Updated 4 months ago
- Vector Quantile Regression☆19Updated last year
- Literature and light wrappers for gaussian process models.☆45Updated 3 years ago
- Collection of resources from each meetup event☆13Updated 3 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆46Updated 3 years ago
- pyWATTS: Python Workflow Automation Tool for Time-Series☆39Updated 5 months ago
- Neural networks for conditional density estimation☆12Updated 4 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆23Updated last year
- ☆14Updated last year
- Implementation of the Gaussian Process Autoregressive Regression Model☆61Updated 3 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆116Updated 11 months ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆21Updated 3 years ago
- Package for fitting Gaussian Process Emulators to multiple output computer simulation results.☆47Updated last year
- ☆18Updated last month
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆26Updated 3 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆38Updated 3 months ago
- Software implementations of engression by Shen and Meinshausen (2023)☆14Updated 3 weeks ago
- A pure python implementation for vine copulas☆15Updated 2 months ago
- Base classes for creating scikit-learn-like parametric objects, and tools for working with them.☆18Updated last week
- ☆46Updated 4 months ago
- ☆28Updated last year
- Probabilistic modeling of tabular data with normalizing flows.☆55Updated 5 months ago
- Conformal Prediction for Time Series with Modern Hopfield Networks☆71Updated 11 months ago
- Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory☆34Updated 2 years ago
- Contains the code to run the different models considered in the paper "Valid prediction intervals for regression problems"☆19Updated 2 years ago
- Implementations of normalizing flows using python and tensorflow☆24Updated 3 years ago
- A multiverse of Prophet models for timeseries☆33Updated this week