Alternatives and similar repositories for agd_exp

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

• chziakas / backbone-learn
  A Library for Scaling Mixed-Integer Optimization-Based Machine Learning.
  ☆12Updated last year
• gugarosa / learnergy
  💡 Learnergy is a Python library for energy-based machine learning models.
  ☆69Updated last month
• ml-jku / quam
  Quantification of Uncertainty with Adversarial Models
  ☆29Updated 2 years ago
• remilepriol / causal-adaptation-speed
  Investigate the speed of adaptation of structural causal models
  ☆15Updated 5 years ago
• XinshaoAmosWang / DeepCriticalLearning
  Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.
  ☆31Updated 3 years ago
• 392781 / scikit-ntk
  Neural Tangent Kernel (NTK) module for the scikit-learn library
  ☆25Updated last year
• tijana-zrnic / cross-ppi
  Cross-prediction-powered inference
  ☆15Updated last year
• MilesCranmer / pysr_scaling_laws
  You should use PySR to find scaling laws. Here's an example.
  ☆33Updated 2 years ago
• jmkuebler / auto-tst
  AutoML Two-Sample Test
  ☆19Updated 3 years ago
• facebookresearch / LANCER
  Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"
  ☆38Updated 2 years ago
• petuum / tuun
  Hyperparameter tuning via uncertainty modeling
  ☆49Updated last year
• microsoft / goodpoints
  A Python package for generating concise, high-quality summaries of a probability distribution
  ☆57Updated 3 weeks ago
• ExpectationMax / sklearn-jax-kernels
  Composable kernels for scikit-learn implemented in JAX.
  ☆47Updated 5 years ago
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆20Updated 3 years ago
• robert-giaquinto / gradient-boosted-normalizing-flows
  We got a stew going!
  ☆27Updated 2 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆122Updated 4 years ago
• juliagusak / neural-ode-norm
  Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"
  ☆16Updated 5 years ago
• pronobis / libspn-keras
  Library for learning and inference with Sum-product Networks utilizing TensorFlow 2.x and Keras
  ☆48Updated 5 months ago
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• probml / JSL
  Jax SSM Library
  ☆48Updated 3 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year
• edwardjhu / improved_wasserstein
  Code for our ICLR Trustworthy ML 2020 workshop paper "Improved Image Wasserstein Attacks and Defenses"
  ☆14Updated 5 years ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆58Updated this week
• vidalt / OCEAN
  OCEAN: Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)
  ☆35Updated 2 months ago
• mathcoding / opt4ds
  Optimization Models and Algorithms
  ☆17Updated 8 months ago
• francescocicala / deep-learning-with-pytorch
  Deep learning lectures I am holding for the MSc on Data Science and Scientific Computing
  ☆15Updated 3 years ago
• closest-git / QuantumForest
  Fast Differentiable Forest lib with the advantages of both decision trees and neural networks
  ☆78Updated 4 years ago
• pyhopper / pyhopper
  PyHopper is a hyperparameter optimizer, made specifically for high-dimensional problems arising in machine learning research.
  ☆85Updated 2 years ago
• mhlr / awesome-jax
  List of awesome JAX resources
  ☆13Updated 3 years ago
• mossr / TikzNeuralNetworks.jl
  Visualize neural networks using TikZ in Julia
  ☆15Updated last year