Alternatives and similar repositories for simpleNN

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

• csinva / disentangled-attribution-curves
  Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
  ☆28Updated 4 years ago
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆34Updated 2 years ago
• nthu-datalab / ml
  ☆14Updated 6 months ago
• guanghelee / iclr19-robust-locally-linear-nets
  "Towards Robust, Locally Linear Deep Networks" (ICLR 2019)
  ☆9Updated 6 years ago
• damaru2 / ntk
  NTK reading group
  ☆87Updated 5 years ago
• ASUS-AICS / LibMultiLabel-Old-Archive
  This library has been moved to https://github.com/ntumlgroup/LibMultiLabel
  ☆153Updated 8 months ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 5 years ago
• OanaMariaCamburu / CanITrustTheExplainer
  ☆18Updated 5 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• SahinLale / StochasticMirrorDescent
  Stochastic Mirror Descent on CIFAR-10
  ☆20Updated 5 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆111Updated 5 years ago
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• Jianbo-Lab / L2X
  ☆124Updated 4 years ago
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆51Updated 3 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 4 years ago
• alshedivat / meta-blocks
  A modular toolbox for meta-learning research with a focus on speed and reproducibility.
  ☆124Updated 2 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• adityashrm21 / information-theory-deep-learning
  Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning
  ☆45Updated 6 years ago
• google-deepmind / mc_gradients
  ☆168Updated 10 months ago
• Thrandis / EKFAC-pytorch
  Repository containing Pytorch code for EKFAC and K-FAC perconditioners.
  ☆143Updated 2 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago
• CecileLiu / Graph-Neural-Networks
  A study group related to GNN
  ☆26Updated 5 years ago
• closest-git / QuantumForest
  Fast Differentiable Forest lib with the advantages of both decision trees and neural networks
  ☆78Updated 3 years ago
• wiseodd / natural-gradients
  Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)
  ☆139Updated 6 years ago
• udellgroup / orie7191
  Materials for ORIE 7191: Topics in Optimization for Machine Learning
  ☆44Updated 6 years ago
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆44Updated 6 years ago
• yaohungt / TransformerDissection
  [EMNLP'19] Summary for Transformer Understanding
  ☆53Updated 5 years ago
• dlg4nlp / dlg4nlp.github.io
  This website is to host a series of tutorials on Deep Learning on Graphs for Natural Language Processing.
  ☆13Updated 2 years ago
• chenhongge / RobustTrees
  [ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
  ☆67Updated 2 years ago
• natalialmg / MMPF
  Implementation of Minimax Pareto Fairness framework
  ☆21Updated 4 years ago