rtanno21609 / AdaptiveNeuralTrees

Related projects ⓘ

Alternatives and complementary repositories for AdaptiveNeuralTrees

• kimhc6028 / soft-decision-tree
  pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
  ☆286Updated 5 years ago
• kingfengji / eForest
  This is the official implementation for the paper 'AutoEncoder by Forest'
  ☆74Updated 6 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆88Updated 5 years ago
• jingxil / Neural-Decision-Forests
  An implementation of the Deep Neural Decision Forests in PyTorch
  ☆155Updated 5 years ago
• Jianbo-Lab / L2X
  ☆124Updated 3 years ago
• xuyxu / Soft-Decision-Tree
  PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.
  ☆96Updated 8 months ago
• lucfra / FAR-HO
  Gradient based hyperparameter optimization & meta-learning package for TensorFlow
  ☆187Updated 4 years ago
• liyu95 / NN_decision_boundary
  On the decision boundary of deep neural networks
  ☆38Updated 6 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆53Updated 5 years ago
• wOOL / DNDT
  Deep Neural Decision Trees
  ☆159Updated 2 years ago
• bsharchilev / influence_boosting
  Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
  ☆67Updated 5 months ago
• kirthevasank / nasbot
  Neural Architecture Search with Bayesian Optimisation and Optimal Transport
  ☆133Updated 5 years ago
• zalandoresearch / pytorch-dilated-rnn
  Dilated RNNs in pytorch
  ☆211Updated 5 years ago
• vodp / py-kmm
  A Python implementation of Kernel Mean Matching data reweighting algorithm
  ☆33Updated 8 years ago
• dtak / tree-regularization-public
  Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"
  ☆78Updated 6 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆48Updated 6 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆139Updated 8 years ago
• marcoancona / DASP
  Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)
  ☆60Updated 5 years ago
• wOOL / DMTRL
  [Code] Deep Multi-task Representation Learning: A Tensor Factorisation Approach
  ☆57Updated 7 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆129Updated 4 years ago
• ermongroup / ssdkl
  Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
  ☆74Updated 5 years ago
• automl / fanova
  Functional ANOVA
  ☆122Updated 7 months ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆110Updated 5 years ago
• shahsohil / DCC
  This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
  ☆209Updated 3 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
• abhiskk / ladder
  Implementation of Ladder Network in PyTorch.
  ☆45Updated 7 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆138Updated 5 months ago
• rdevon / cortex
  A machine learning library for PyTorch
  ☆92Updated 2 years ago
• vsyrgkanis / optimistic_GAN_training
  ☆44Updated 6 years ago
• spiglerg / pyMeta
  Library to manage machine learning problems as `Tasks' and to sample from Task distributions. Includes Tensorflow implementation of impli…
  ☆48Updated 2 years ago