A variational method for fast, approximate inference for stochastic differential equations.
☆45Feb 3, 2026Updated last month
Alternatives and similar repositories for VIforSDEs
Users that are interested in VIforSDEs are comparing it to the libraries listed below
Sorting:
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆24Apr 20, 2019Updated 6 years ago
- ☆12Feb 20, 2021Updated 5 years ago
- ☆14Oct 7, 2019Updated 6 years ago
- Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Sch…☆13Nov 7, 2022Updated 3 years ago
- Kalman Filter for ARX or NARX models' parameters estimation.☆15Dec 10, 2019Updated 6 years ago
- Developing efficient Bayesian phylogenetic inference methods☆12Dec 21, 2019Updated 6 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆156Feb 20, 2020Updated 6 years ago
- ☆13Oct 31, 2021Updated 4 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Sep 29, 2020Updated 5 years ago
- Implementation of Feature Saliency Hidden Markov Model (Adams, et al, 2016)☆14Dec 8, 2022Updated 3 years ago
- Codes for Hilbert space reduced-rank GP regression☆16Jul 30, 2019Updated 6 years ago
- Bayer, Friz, Gassiat, Martin, Stemper (2017). A regularity structure for finance.☆12Sep 29, 2017Updated 8 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Jul 4, 2024Updated last year
- My PhD thesis. I defended on the 30th of October, 2020! See https://github.com/eleurent/phd-defense/☆16Sep 21, 2021Updated 4 years ago
- Implementation of MAML in numpy, deriving gradients and implementing backprop manually☆14Nov 15, 2018Updated 7 years ago
- A MATLAB implementation of a variable projection algorithm for nonlinear least squares problems☆15Oct 16, 2018Updated 7 years ago
- A list (quite disorganized for now) of papers tackling the Bayesian estimation of Ito processes (and their discrete time version)☆16Jul 10, 2020Updated 5 years ago
- ☆17Aug 2, 2022Updated 3 years ago
- Code repository for the AISTATS 2021 paper "Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms"☆15Mar 20, 2021Updated 4 years ago
- Deep multistep methods to solve BSDEs of first and second order for the approximation of PDE solutions☆20May 29, 2020Updated 5 years ago
- Machine Learning tools for Space Weather and Plasma Physics☆17Sep 1, 2022Updated 3 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Jul 9, 2018Updated 7 years ago
- ☆20Mar 23, 2020Updated 5 years ago
- Example codes for the book Applied Stochastic Differential Equations☆206Oct 27, 2025Updated 4 months ago
- Inference Combinators in JAX☆52May 17, 2025Updated 9 months ago
- BlackScholes Model, with Montecarlo implmented in python with TensorFlow☆18Jan 5, 2016Updated 10 years ago
- Gaussian process time-frequency analysis toy examples☆17Apr 5, 2019Updated 6 years ago
- Active inference implementation of dynamic multi-armed bandits☆20Jun 25, 2025Updated 8 months ago
- Main component extraction for outlier detection☆20Dec 6, 2020Updated 5 years ago
- ☆19Jun 11, 2020Updated 5 years ago
- Tools to generate and study moment equations for any chemical reaction network using various moment closure approximations☆49Dec 16, 2025Updated 2 months ago
- Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).☆20Jun 8, 2021Updated 4 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Jan 2, 2021Updated 5 years ago
- 🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…☆43Mar 24, 2023Updated 2 years ago
- Minimax Optimization, Stackelberg Games, Generative Adversarial Networks☆19Feb 14, 2020Updated 6 years ago
- ☆20Apr 14, 2017Updated 8 years ago
- Bayesian Inference and parameter estimation in quant finance.☆43Feb 18, 2019Updated 7 years ago
- Deep Probabilistic Koopman: long-term time-series forecasting under quasi-periodic uncertainty☆24Nov 3, 2021Updated 4 years ago
- The hourly demand and supply of electricity in the US☆26May 26, 2021Updated 4 years ago