Alternatives and similar repositories for OccamNet_Public

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

• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆55Updated last year
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 years ago
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆51Updated 4 years ago
• jamesvuc / jax-bayes
  Bayesian inference with Python and Jax.
  ☆34Updated 2 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 3 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆35Updated 3 years ago
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 6 months ago
• MilesCranmer / pysr_paper
  A paper describing the implementation of PySR and SymbolicRegression.jl
  ☆61Updated last year
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆53Updated 2 years ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆42Updated 5 years ago
• glajoie / MAT6115_Dynamical_Systems
  Support material for MAT6115, Université de Montréal, Fall 2018
  ☆27Updated last year
• alonfnt / pcax
  Differentiable Principal Component Analysis (PCA) implementation in JAX
  ☆29Updated 6 months ago
• facebookresearch / bo_pr
  Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
  ☆74Updated 3 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆62Updated last year
• MilesCranmer / sympy2jax
  Turning SymPy expressions into JAX functions
  ☆45Updated 4 years ago
• google-research / hyperbo
  Pre-trained Gaussian processes for Bayesian optimization
  ☆97Updated 6 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• omron-sinicx / srsd-benchmark
  [DMLR] Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery
  ☆37Updated last year
• kazukiosawa / ngd_in_wide_nn
  simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…
  ☆15Updated 5 years ago
• alexOarga / haiku-geometric
  A collection of graph neural networks implementations in JAX
  ☆35Updated last year
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 3 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆24Updated 2 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆85Updated last year
• alonfnt / bayex
  Minimal Implementation of Bayesian Optimization in JAX
  ☆98Updated 6 months ago
• google-research / gpax
  ☆31Updated last year
• EvoConJP / CMA-ES_with_Margin
  (GECCO 2022) CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization
  ☆31Updated last year
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆43Updated 4 years ago
• mazy1998 / Solving-Optimization-Problems-with-JAX
  Solving Optimization Problems with JAX, code and PDF
  ☆16Updated 5 years ago