Alternatives and similar repositories for DNDT:

Users that are interested in DNDT are comparing it to the libraries listed below

• rtanno21609 / AdaptiveNeuralTrees
  Adaptive Neural Trees
  ☆151Updated 5 years ago
• Jianbo-Lab / L2X
  ☆125Updated 3 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆130Updated 4 years ago
• xuyxu / Soft-Decision-Tree
  PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.
  ☆101Updated last year
• anonICLR2020 / node
  ☆26Updated 5 years ago
• bsharchilev / influence_boosting
  Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
  ☆67Updated 9 months ago
• automl / BOAH
  BOAH: Bayesian Optimization & Analysis of Hyperparameters
  ☆67Updated 4 years ago
• closest-git / QuantumForest
  Fast Differentiable Forest lib with the advantages of both decision trees and neural networks
  ☆78Updated 3 years ago
• udellgroup / oboe
  An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
  ☆82Updated 3 years ago
• aiwabdn / pygln
  Python implementation of GLN in different frameworks
  ☆98Updated 4 years ago
• sbadirli / GrowNet
  ☆201Updated 3 years ago
• lmartak / distill-nn-tree
  Distillation of Neural Network Into a Soft Decision Tree
  ☆65Updated 5 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆69Updated 5 years ago
• rcamino / multi-categorical-gans
  Code for the paper "Generating Multi-Categorical Samples with Generative Adversarial Networks"
  ☆49Updated last year
• steveli / misgan
  MisGAN: Learning from Incomplete Data with GANs
  ☆80Updated last year
• kingfengji / mGBDT
  This is the official clone for the implementation of the NIPS18 paper Multi-Layered Gradient Boosting Decision Trees (mGBDT) .
  ☆103Updated 6 years ago
• kimhc6028 / soft-decision-tree
  pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
  ☆296Updated 6 years ago
• kingfengji / eForest
  This is the official implementation for the paper 'AutoEncoder by Forest'
  ☆75Updated 6 years ago
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆202Updated 3 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆130Updated 4 years ago
• authors-1901-10912 / A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms
  Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"
  ☆126Updated 6 years ago
• jingxil / Neural-Decision-Forests
  An implementation of the Deep Neural Decision Forests in PyTorch
  ☆160Updated 5 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆145Updated 9 months ago
• brendanhasz / probflow
  A Python package for building Bayesian models with TensorFlow or PyTorch
  ☆173Updated 2 years ago
• hcarlens / pytorch-tabular
  Some examples of using PyTorch for tabular data
  ☆65Updated 4 years ago
• lethaiq / GRACE_KDD20
  GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …
  ☆21Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• rsheth80 / pmf-automl
  Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.
  ☆39Updated 3 years ago
• Qwicen / node
  Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
  ☆486Updated 4 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆60Updated 4 years ago