rtanno21609 / AdaptiveNeuralTreesLinks
Adaptive Neural Trees
☆155Updated 6 years ago
Alternatives and similar repositories for AdaptiveNeuralTrees
Users that are interested in AdaptiveNeuralTrees are comparing it to the libraries listed below
Sorting:
- pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"☆302Updated 6 years ago
- Deep Neural Decision Trees☆163Updated 3 years ago
- Gradient based hyperparameter optimization & meta-learning package for TensorFlow☆190Updated 5 years ago
- An implementation of the Deep Neural Decision Forests in PyTorch☆165Updated 6 years ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆135Updated 6 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆128Updated 5 years ago
- Distance Metric Learning Algorithms for Python☆174Updated 4 years ago
- Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"☆79Updated 7 years ago
- On the decision boundary of deep neural networks☆38Updated 7 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆61Updated 6 years ago
- PyTorch implementation of Neural Processes☆88Updated 6 years ago
- Distillation of Neural Network Into a Soft Decision Tree☆65Updated 5 years ago
- A Python implementation of Kernel Mean Matching data reweighting algorithm☆33Updated 9 years ago
- ☆124Updated 4 years ago
- Dilated RNNs in pytorch☆211Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 6 years ago
- Code for experiments regarding importance sampling for training neural networks☆329Updated 3 years ago
- Tensorflow implementation of a Tree☆35Updated 6 years ago
- This is the official implementation for the paper 'AutoEncoder by Forest'☆75Updated 7 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Hypergradient descent☆148Updated last year
- ☆80Updated 7 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Active Learning on Image Data using Bayesian ConvNets☆138Updated 8 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Implementation of soft parameter sharing for neural networks☆70Updated 4 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- tensorflow implementation of the Wasserstein (aka optimal transport) distance☆72Updated 4 years ago
- PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.☆103Updated last year
- Example code for the paper "Understanding deep learning requires rethinking generalization"☆178Updated 5 years ago