praritagarwal / Visualizing-CNN-LayersLinks
Project to visualize the kernels and the outputs of the individual layers of a CNN built in pytorch.
☆18Updated 5 years ago
Alternatives and similar repositories for Visualizing-CNN-Layers
Users that are interested in Visualizing-CNN-Layers are comparing it to the libraries listed below
Sorting:
- Measuring the robustness of compressive sensing methods (including deep-learning-based ones) for image reconstruction.☆32Updated 4 years ago
- (ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks☆51Updated 3 years ago
- Adaptive wavelet pooling for CNN in PyTorch, AISTATS 2021.☆32Updated 4 years ago
- Random Mesh Projectors for Inverse Problems☆24Updated 4 years ago
- ☆35Updated 4 years ago
- 1D Wasserstein Statistical Loss in Pytorch☆28Updated 5 years ago
- A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.☆92Updated 9 months ago
- Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)☆18Updated last year
- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data (Pytorch)☆19Updated 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…☆59Updated 2 years ago
- Variational Autoencoders trained on the SVHN and FashionMNIST data-sets implemented in PyTorch☆32Updated 2 years ago
- Adaptive, interpretable wavelets across domains (NeurIPS 2021)☆84Updated 4 years ago
- This is official Pytorch implementation of "Uncertainty quantification in medical image segmentation with Normalizing Flows", Raghavendra…☆30Updated 3 years ago
- Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning, AAAI-SA'19☆29Updated 6 years ago
- Fourier Image Transformer (FIT) can solve relevant image analysis tasks in Fourier space.☆101Updated 3 years ago
- ☆24Updated 4 years ago
- Representation Learning with Diffusion Models☆33Updated 3 years ago
- ☆16Updated 6 years ago
- Multi-Channel Variational Auto Encoder: A Bayesian Deep Learning Framework for Modeling High-Dimensional Heterogeneous Data.☆32Updated 4 years ago
- Neuromorphologicaly Preserving Volumetric Data Encoding Using VQ-VAE☆16Updated 3 years ago
- Categorical Variational Auto-encoders in PyTorch☆22Updated 4 years ago
- Revealing Hidden Patterns in Deep Neural Network Feature Space Continuum via Manifold Learning (Nature Communications, 2023)☆28Updated 2 years ago
- Code for the paper: Complex-Valued Autoencoders for Object Discovery☆57Updated 2 years ago
- Complex tensor and complex functions for pytorch.☆49Updated 3 years ago
- A toy example of VAE-regression network☆74Updated 5 years ago
- A PyTorch add-on for working with image mappings and displacement fields, including Spatial Transformers☆51Updated 3 years ago
- An implementation of Denoising Variational AutoEncoder with Topological loss☆32Updated 5 years ago
- An implementation of approximate convolutional sparse coding (CSC) based on paper: https://arxiv.org/abs/1711.00328☆42Updated last month
- Official Code for "Invert to Learn to Invert" that allows training of invertible networks without storing activations☆37Updated 5 years ago
- Implementation of "Learning Multiscale Convolutional Dictionaries for Image Reconstruction", IEEE Transaction On Computational Imaging, 2…☆32Updated 2 years ago