google-research / spherical-cnn
☆115Updated 3 months ago
Alternatives and similar repositories for spherical-cnn:
Users that are interested in spherical-cnn are comparing it to the libraries listed below
- Differentiable and accelerated spherical transforms with JAX☆146Updated this week
- Running Jax in PyTorch Lightning☆90Updated 3 months ago
- Multiple dispatch over abstract array types in JAX.☆115Updated last month
- Run PyTorch in JAX. 🤝☆232Updated last month
- Differentiable signal processing on the sphere for PyTorch☆444Updated last month
- Differentiable and gpu enabled fast wavelet transforms in JAX.☆43Updated 8 months ago
- Code repository of the paper "Clifford-Steerable Convolutional Neural Networks"☆47Updated 7 months ago
- A minimal implementation of Equivariant Neural Fields (https://arxiv.org/abs/2406.05753).☆23Updated last month
- Stencil computations in JAX☆70Updated last year
- Code for the paper Universal Physics Transformers☆99Updated last month
- Matrix-free linear algebra in JAX.☆116Updated 2 months ago
- Stainless neural networks in JAX☆33Updated this week
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- Graph neural networks in JAX.☆67Updated 9 months ago
- Pytorch-like dataloaders for JAX.☆77Updated 5 months ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆123Updated 6 months ago
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆83Updated this week
- Automatic Functional Differentiation in JAX☆67Updated this week
- Official implementation of Stochastic Taylor Derivative Estimator (STDE) NeurIPS2024☆102Updated 4 months ago
- Code for paper "Multiple Physics Pretraining for Physical Surrogate Models☆150Updated 3 months ago
- ☆153Updated last year
- Diffusion models in PyTorch☆97Updated this week
- Codomain attention neural operator for single to multi-physics PDE adaptation.☆49Updated last week
- Official repository of Implicit Neural Convolutional Kernels for Steerable CNNs, Zhdanov et al.☆28Updated last month
- Code for the book "The Elements of Differentiable Programming".☆77Updated last week
- Wraps PyTorch code in a JIT-compatible way for JAX. Supports automatically defining gradients for reverse-mode AutoDiff.☆47Updated last month
- Official implementation of Score-based Data Assimilation☆52Updated last year
- Fully and Partially Bayesian Neural Nets☆66Updated 2 weeks ago
- Unleash the true power of scheduling☆30Updated 2 weeks ago
- JAX bindings to the Flatiron Institute Non-uniform Fast Fourier Transform (FINUFFT) library☆89Updated 3 weeks ago