Alternatives and similar repositories for DynamicBlocks

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

• jinnerbichler / g-research-challenge
  Project for the financial forecasting challenge from G-Research (https://financialforecasting.gresearch.co.uk/).
  ☆7Updated 7 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆41Updated 3 years ago
• gauravdhama / eigengame_deepmind
  A basic implementation of the paper Eigengame : PCA as a Nash Equilibrium
  ☆21Updated 4 years ago
• ShuaiGuo16 / Gaussian-Process
  Implementing a Gaussian Process regression model from scratch
  ☆23Updated 4 years ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆15Updated 2 years ago
• neildhir / DCBO
  Dynamic causal Bayesian optimisation
  ☆39Updated 2 years ago
• MachineLearningJournalClub / LearningNLP
  Some Tutorials & in depth analysis of NLP's algorithms with an ethical flavour
  ☆14Updated 3 years ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 2 years ago
• christopher-beckham / coms-are-energy-models
  Official code for paper: Conservative objective models are a special kind of contrastive divergence-based energy model
  ☆14Updated last year
• datasig-ac-uk / signature_applications
  Example applications of path signatures
  ☆40Updated 3 months ago
• aormorningstar / GenerativeNeuralNets
  Implementation of restricted Boltzmann machine, deep Boltzmann machine, deep belief network, and deep restricted Boltzmann network models…
  ☆12Updated 4 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆32Updated 3 years ago
• msuzen / bristol
  Parallel random matrix tools and complexity for deep learning
  ☆33Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• vr308 / GPLVM
  Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
  ☆15Updated 4 years ago
• operalib / operalib
  Learning with operator-valued kernels
  ☆22Updated 2 years ago
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 3 years ago
• Bostanabad-Research-Group / GP-for-pde-solving
  ☆18Updated 8 months ago
• duke-mlss / Duke-MLWS-2019
  Duke Machine Learning Winter School 2019
  ☆27Updated 6 years ago
• smeznar / HVAE
  An approach for embedding hierarhical structures into a continuous vector space using variational autoencoders.
  ☆28Updated last week
• icme / cme258
  Libraries for Scientific Computing
  ☆10Updated 6 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• OxfordML / bayesquad
  Library for Bayesian Quadrature
  ☆32Updated 6 years ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆58Updated 3 weeks ago
• ronikobrosly / scipy_2023_causal_inference_tutorial
  Materials for a proposed Causal Inference Tutorial session at SciPy 2023
  ☆12Updated 2 years ago
• ahmedmalaa / Symbolic-Metamodeling
  Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
  ☆50Updated 5 years ago
• jinglingli / nn-extrapolate
  ☆13Updated 2 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated 2 years ago
• facebookresearch / alebo
  Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization
  ☆41Updated 3 years ago