ai4iacts / hexagdlyLinks
Process hexagonally sampled data with PyTorch
☆94Updated 4 years ago
Alternatives and similar repositories for hexagdly
Users that are interested in hexagdly are comparing it to the libraries listed below
Sorting:
- ☆64Updated 5 years ago
- Composable kernels for scikit-learn implemented in JAX.☆44Updated 4 years ago
- ☆36Updated 2 years ago
- Streaming approximate histograms with Python.☆43Updated 3 years ago
- General-purpose dimensionality reduction and manifold learning tool based on Variational Autoencoder, implemented in TensorFlow.☆157Updated 7 months ago
- Implementations of normalizing flows using python and tensorflow☆24Updated 8 months ago
- Tensorflow 2.0 implementation of Fourier Feature Mapping Networks.☆43Updated 5 years ago
- Documentation:☆121Updated 2 years ago
- Automatic differentiation + optimization☆103Updated 6 years ago
- Interactively retrieve data from sacred experiments.☆82Updated 2 weeks ago
- Interpolation routines in Pytorch.☆111Updated 4 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆107Updated 4 years ago
- ☆31Updated 2 years ago
- dask-pytorch-ddp is a Python package that makes it easy to train PyTorch models on dask clusters using distributed data parallel.☆59Updated 4 years ago
- Official PyTorch implementation for our NeurIPS 2019 paper, Diffeomorphic Temporal Alignment Nets. TensorFlow\Keras version is available…☆68Updated 9 months ago
- Windowed alignment of time series at the speed of light☆29Updated 4 years ago
- A temporary repository hosting a pomegranate re-write using PyTorch as the backend.☆72Updated 2 years ago
- A Python toolkit for (simulation-based) inference and the mechanization of science.☆53Updated 3 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep…☆151Updated 4 years ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆21Updated 4 years ago
- Predict and analyze cellular automata using convolutional neural networks☆81Updated 4 years ago
- Automate issue discovery for your projects against Lightning nightly and releases.☆46Updated 3 months ago
- Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST☆64Updated 7 years ago
- 👩 Pytorch and Jax code for the Madam optimiser.☆51Updated 4 years ago
- A Cython interface to FLANN☆24Updated 4 years ago
- Explaining dimensionality results using SHAP values☆54Updated 7 months ago
- Toolkit for building predictive workflows on top of pydata (pandas, scikit-learn, pytorch, keras, etc.).☆72Updated 5 months ago
- Weighted Principal Component Analysis (PCA) in Python☆156Updated 7 years ago
- Advanced random forest methods in Python☆57Updated last year