tscohen / gconv_experimentsLinks
Experiments with Group Equivariant Convolutional Networks
☆120Updated 6 years ago
Alternatives and similar repositories for gconv_experiments
Users that are interested in gconv_experiments are comparing it to the libraries listed below
Sorting:
- Group Equivariant Convolutional Neural Networks☆363Updated 4 years ago
- Code for paper "Convergent Learning: Do different neural networks learn the same representations?"☆86Updated 9 years ago
- Deep Translation and Rotation Equivariance☆268Updated 6 years ago
- Visualizing Deep Neural Network Decisions: Prediction Difference Analysis☆118Updated 7 years ago
- ☆82Updated 7 years ago
- Learning Deep Parsimonious Representations, Deep Learning, Clustering, NIPS 2016☆14Updated 5 years ago
- Second-order optimiser for deep networks☆76Updated 6 years ago
- Structured Receptive Fields in Convolutional Neural Networks☆47Updated 7 years ago
- Implementation of Sequential Variational Autoencoder☆88Updated 7 years ago
- A Lasagne layer (and supporting Theano Ops) for the CRF-as-RNN layer.☆49Updated 4 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Implementation of auxiliary deep generative models for semi-supervised learning☆28Updated 9 years ago
- A Tensorfflow implementation of Attend, Infer, Repeat☆81Updated 6 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 7 years ago
- ☆69Updated 8 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆252Updated 6 years ago
- Dropout As A Bayesian Approximation: Code☆202Updated 10 years ago
- Implementation of Coulomb GANs☆62Updated 3 years ago
- Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training o…☆149Updated 8 years ago
- Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps☆42Updated 6 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- Capsule network with variations. Originally proposed by Tieleman & Hinton : http://www.cs.toronto.edu/~tijmen/tijmen_thesis.pdf☆170Updated 7 years ago
- Generative moment matching networks☆150Updated 9 years ago
- ☆121Updated 8 years ago
- ☆219Updated 7 years ago
- PixelVAE with or without regularization☆66Updated 8 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Tensorflow implementation of Generative Latent Optimization (GLO) proposed by Facebook AI Research☆95Updated 7 years ago