kormilitzin / the-signature-method-in-machine-learning
Foundations and Applications
☆96Updated 4 years ago
Alternatives and similar repositories for the-signature-method-in-machine-learning:
Users that are interested in the-signature-method-in-machine-learning are comparing it to the libraries listed below
- Code for "Deep Signature Transforms" (NeurIPS 2019)☆93Updated 9 months ago
- Iterated integral signature calculations☆104Updated 5 months ago
- Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)☆270Updated last year
- Code for: "A Generalised Signature Method for Time Series"☆63Updated last year
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- A Brief Introduction to Path Signatures for Machine Learning Practitioners☆48Updated 3 years ago
- Example applications of path signatures☆38Updated 3 weeks ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- ☆26Updated last year
- esig python package☆48Updated 4 months ago
- fast parameter estimation for simpler Hawkes processes☆70Updated 2 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆115Updated 3 years ago
- Differentiable computations for the signature-PDE-kernel on CPU and GPU.☆54Updated 11 months ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆195Updated 2 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- Variational Autoencoder for Dimensionality Reduction of Time-Series☆186Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-40…☆56Updated 5 years ago
- Learning Hawkes Processes from a Handful of Events☆13Updated last year
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆77Updated last year
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆37Updated 3 years ago
- Group Lasso implementation following the scikit-learn API☆106Updated 10 months ago
- Market simulator☆60Updated 4 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- Random Forests for Density Estimation in Python☆25Updated last year