Alternatives and similar repositories for soft-decision-tree:

Users that are interested in soft-decision-tree are comparing it to the libraries listed below

• xuyxu / Soft-Decision-Tree
  PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.
  ☆100Updated 11 months ago
• kirthevasank / nasbot
  Neural Architecture Search with Bayesian Optimisation and Optimal Transport
  ☆133Updated 6 years ago
• rtanno21609 / AdaptiveNeuralTrees
  Adaptive Neural Trees
  ☆151Updated 5 years ago
• lucfra / FAR-HO
  Gradient based hyperparameter optimization & meta-learning package for TensorFlow
  ☆188Updated 4 years ago
• ericjang / gumbel-softmax
  categorical variational autoencoder using the Gumbel-Softmax estimator
  ☆429Updated 7 years ago
• keskarnitish / large-batch-training
  Code to reproduce some of the figures in the paper "On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima"
  ☆138Updated 7 years ago
• marcoancona / DASP
  Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)
  ☆61Updated 5 years ago
• Jianbo-Lab / L2X
  ☆124Updated 3 years ago
• yaringal / ConcreteDropout
  Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
  ☆248Updated 6 years ago
• liupeng3425 / interpretable-research
  I collected some papers about interpretable CNN and reorganized them here.
  ☆128Updated 6 years ago
• lmartak / distill-nn-tree
  Distillation of Neural Network Into a Soft Decision Tree
  ☆64Updated 5 years ago
• wOOL / DNDT
  Deep Neural Decision Trees
  ☆161Updated 2 years ago
• zalandoresearch / pytorch-dilated-rnn
  Dilated RNNs in pytorch
  ☆212Updated 5 years ago
• ikostrikov / pytorch-meta-optimizer
  A PyTorch implementation of Learning to learn by gradient descent by gradient descent
  ☆312Updated 6 years ago
• dtak / tree-regularization-public
  Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"
  ☆78Updated 7 years ago
• idiap / importance-sampling
  Code for experiments regarding importance sampling for training neural networks
  ☆324Updated 3 years ago
• jingxil / Neural-Decision-Forests
  An implementation of the Deep Neural Decision Forests in PyTorch
  ☆159Updated 5 years ago
• AMLab-Amsterdam / L0_regularization
  Learning Sparse Neural Networks through L0 regularization
  ☆238Updated 4 years ago
• pluskid / fitting-random-labels
  Example code for the paper "Understanding deep learning requires rethinking generalization"
  ☆177Updated 4 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆145Updated 8 months ago
• L0SG / relational-rnn-pytorch
  An implementation of DeepMind's Relational Recurrent Neural Networks (NeurIPS 2018) in PyTorch.
  ☆245Updated 6 years ago
• zygmuntz / hyperband
  Tuning hyperparams fast with Hyperband
  ☆593Updated 6 years ago
• benoitdescamps / Neural-Tree
  Tensorflow implementation of a Tree
  ☆36Updated 5 years ago
• mbinkowski / nntimeseries
  ☆209Updated 6 years ago
• ShiyuLiang / odin-pytorch
  Principled Detection of Out-of-Distribution Examples in Neural Networks
  ☆201Updated 7 years ago
• automl / fanova
  Functional ANOVA
  ☆122Updated this week
• bayesgroup / variational-dropout-sparsifies-dnn
  Sparse Variational Dropout, ICML 2017
  ☆313Updated 4 years ago
• KarenUllrich / Tutorial_BayesianCompressionForDL
  A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).
  ☆205Updated 6 years ago
• lucfra / RFHO
  Gradient-based hyperparameter optimization package with TensorFlow
  ☆51Updated 5 years ago
• code-terminator / DilatedRNN
  Tensorflow implementation for DilatedRNN
  ☆346Updated 7 years ago