ZhengyuLiang24 / Conv4d-PyTorch
Implementation of Conv4d for PyTorch
☆40Updated 2 years ago
Alternatives and similar repositories for Conv4d-PyTorch
Users that are interested in Conv4d-PyTorch are comparing it to the libraries listed below
Sorting:
- wavelet implicit neural representations☆158Updated last year
- Implementation of "Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains" by Tancik et al.☆91Updated 2 years ago
- [ICML 2022] "Neural Implicit Dictionary via Mixture-of-Expert Training" by Peihao Wang, Zhiwen Fan, Tianlong Chen, Zhangyang Wang☆40Updated last year
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains☆47Updated 4 years ago
- Source code for Fathony, Sahu, Willmott, & Kolter, "Multiplicative Filter Networks", ICLR 2021.☆94Updated 4 years ago
- Transformers as Meta-Learners for Implicit Neural Representations, in ECCV 2022☆152Updated 2 years ago
- ☆12Updated last year
- [NeurIPS 2021] SNIPS: Solving Noisy Inverse Problems Stochastically☆51Updated 2 years ago
- Functional N-dimensional convolution in Pytorch, recursively calling convNd until reaching conv3d.☆78Updated 3 weeks ago
- Source code of "A structured dictionary perspective on implicit neural representations"☆58Updated 3 years ago
- U-Net architecture with Kolmogorov-Arnold Convolutions (KA convolutions)☆35Updated last year
- The official repository for Neural Fourier Filter Bank (CVPR 2023)☆68Updated last year
- ☆78Updated 4 years ago
- Kolmogorov-Arnold networks (KAN) as implicit functions (like NeRF but simpler)☆14Updated last year
- Rudimentary Conv4D Layer Implementation for PyTorch☆39Updated 6 years ago
- ☆16Updated 3 years ago
- The official implementation of Generalizable Implicit Neural Representations with Instance Pattern Composers(CVPR’23 highlight).☆39Updated 2 years ago
- Code related to the paper "Deep Equilibrium Architectures for Inverse Problems in Imaging"☆37Updated 3 years ago
- Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with…☆56Updated 2 years ago
- Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).☆35Updated 3 years ago
- A Convolutional Variational Autoencoder (CVAE) for 3D CFD data reconstruction and generation.☆40Updated 3 years ago
- [NeurIPS 2022] "Signal Processing for Implicit Neural Representations" by Dejia Xu*, Peihao Wang*, Yifan Jiang, Zhiwen Fan, Zhangyang Wan…☆53Updated 2 years ago
- A PyTorch implementation of the ECCV 2022 paper "Neural Image Representations for Multi-Image Fusion and Layer Separation"☆22Updated 2 years ago
- ☆29Updated 2 years ago
- ☆27Updated 3 years ago
- A PyTorch implementation of adaptive Monte Carlo Optimal Transport algorithm☆36Updated last year
- InverseBench (ICLR 2025 spotlight)☆42Updated 3 weeks ago
- Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation☆62Updated 2 years ago
- 🚀 A powerful library for efficient training of Neural Fields at scale.☆29Updated last year
- Pytorch implementation of COIN++ 🍁☆71Updated 2 years ago