Alternatives and similar repositories for sampling-methods-numpy

Users that are interested in sampling-methods-numpy are comparing it to the libraries listed below

• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• ritchieng / eigenvectors-from-eigenvalues
  PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.
  ☆98Updated 4 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆151Updated 2 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• twhughes / Symbolic-Regression
  predicting equations from raw data with deep learning
  ☆57Updated 6 years ago
• gcucurull / jax-gcn
  Graph Convolutional Networks in JAX
  ☆33Updated 4 years ago
• luckystarufo / multiscale_HiTS
  ☆73Updated 5 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆121Updated 2 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• theevann / dl4sci-pytorch-webinar
  ☆56Updated 5 years ago
• distillpub / post--bayesian-optimization
  Exploring Bayesian Optimization
  ☆76Updated 4 years ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 3 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆43Updated 4 years ago
• QUVA-Lab / COMBO
  ☆50Updated last year
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆70Updated 7 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• martenlienen / finite-element-networks
  Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…
  ☆69Updated last year
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• kd383 / GPML_SLD
  Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)
  ☆18Updated 7 years ago
• gwgundersen / random-fourier-features
  Code for random Fourier features based on Rahimi and Recht's 2007 paper.
  ☆58Updated 4 years ago
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆51Updated 4 years ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆58Updated this week
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 5 years ago
• facebookresearch / robust_mobo
  Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"
  ☆56Updated 3 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 6 years ago
• marcovirgolin / SimpleGP
  Simple Genetic Programming for Symbolic Regression in Python3
  ☆27Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago