Alternatives and similar repositories for lfbo

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

• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆52Updated 2 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 5 years ago
• brandontrabucco / design-baselines
  Baselines for Model-Based Optimization
  ☆55Updated 3 years ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆47Updated 2 years ago
• facebookresearch / amortized-optimization-tutorial
  Tutorial on amortized optimization for learning to optimize over continuous domains
  ☆248Updated 3 months ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆49Updated 10 months ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• cunningham-lab / igr
  ☆30Updated 5 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 4 years ago
• jungtaekkim / bayeso-benchmarks
  Benchmark functions for Bayesian optimization
  ☆37Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 4 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• wgrathwohl / VERA
  ☆64Updated last year
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆58Updated 4 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆78Updated 2 years ago
• ChunyuanLI / SVGD
  Tensorflow implementation of Stein Variational Gradient Descent (SVGD)
  ☆26Updated 8 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 5 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• jonasrothfuss / meta_learning_pacoh
  Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds
  ☆26Updated last year
• alecwangcq / KFAC-Pytorch
  Pytorch implementation of KFAC and E-KFAC (Natural Gradient).
  ☆132Updated 6 years ago
• yilundu / improved_contrastive_divergence
  [ICML'21] Improved Contrastive Divergence Training of Energy Based Models
  ☆69Updated 3 years ago
• choidami / sst
  ☆50Updated 5 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated last year
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• ltiao / bore
  Bayesian Optimization with Density-Ratio Estimation
  ☆24Updated 3 years ago
• GFNOrg / EB_GFN
  Code for our paper "Generative Flow Networks for Discrete Probabilistic Modeling"
  ☆87Updated 2 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆54Updated 5 years ago