Alternatives and similar repositories for bmi

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

• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆94Updated 2 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated 7 months ago
• akekic / causal-component-analysis
  ☆25Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆70Updated 8 months ago
• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆61Updated this week
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆94Updated 3 years ago
• jongharyu / neural-svd
  Official PyTorch implementation of NeuralSVD (ICML 2024)
  ☆20Updated last year
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• mfederici / torch-mist
  Implementation of a PyTorch Mutual Information Estimation Toolkit
  ☆22Updated last year
• CUAI / Riemannian-Residual-Neural-Networks
  [NeurIPS 2023] Riemannian Residual Neural Networks (https://arxiv.org/abs/2006.10254)
  ☆22Updated last year
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated 2 years ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆152Updated last month
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆40Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• juangamella / causal-chamber
  Public dataset repository for the Causal Chamber Project
  ☆54Updated 2 months ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆23Updated 5 years ago
• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆80Updated last year
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆57Updated 2 months ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• andres-fr / skerch
  Sketched linear operations for PyTorch
  ☆100Updated 2 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• konstantinos-p / Bayesian-Neural-Networks-Reading-List
  A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…
  ☆57Updated 2 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆245Updated last year
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆35Updated 4 months ago
• automl / PFNs
  Our maintained PFN repository. Come here to train SOTA PFNs.
  ☆125Updated 3 months ago
• mariuslindegaard / Intermediate_Neural_Collapse
  (ICML 2023) Feature learning in deep classifiers through Intermediate Neural Collapse: Accompanying code
  ☆15Updated 2 years ago