Alternatives and similar repositories for multi_task_neural_processes:

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

• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆28Updated 9 months ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆75Updated 2 years ago
• volagold / nce
  Noise Contrastive Estimation (NCE) in PyTorch
  ☆32Updated 2 months ago
• ruiqigao / recovery_likelihood
  ☆50Updated 4 years ago
• jihoontack / SiMT
  Meta-Learning with Self-Improving Momentum Target (NeurIPS 2022)
  ☆23Updated 2 years ago
• jinxu06 / metafun-tensorflow
  Code for "MetaFun: Meta-Learning with Iterative Functional Updates"
  ☆14Updated 4 years ago
• AndreevP / FRCL
  Functional Regularisation for Continual Learning with Gaussian Processes
  ☆14Updated 4 years ago
• singhgautam / snp
  This is the official source code for Sequential Neural Processes.
  ☆40Updated 2 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• kyungmnlee / RenyiCL
  Contrastive self-supervised learning using Rényi divergence
  ☆12Updated 2 years ago
• matwilso / maml_numpy
  Implementation of MAML in numpy, deriving gradients and implementing backprop manually
  ☆14Updated 6 years ago
• a7b23 / H-Divergence
  ☆21Updated 2 years ago
• MingyuKim87 / NPwSA
  Official PyTorch implementation of NPwSA: "Neural Processes with Stochastic Attention: Paying more attention to the context dataset (ICLR…
  ☆10Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• brendel-group / cl-ica
  Code for the paper "Contrastive Learning Inverts the Data Generating Process".
  ☆90Updated 9 months ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆44Updated 2 years ago
• KingJamesSong / latent-flow
  NeurIPS23 "Flow Factorized Representation Learning"
  ☆35Updated 6 months ago
• rosinality / igebm-pytorch
  Implicit Generation and Generalization in Energy Based Models in PyTorch
  ☆65Updated 6 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 3 years ago
• hankook / CLEL
  ☆15Updated 2 years ago
• chingyaoc / InfoOT
  [ICML2023] InfoOT: Information Maximizing Optimal Transport
  ☆40Updated 2 years ago
• chen-hao-chao / dlsm
  [ICLR 2022] Denoising Likelihood Score Matching for Conditional Score-based Data Generation
  ☆9Updated 4 months ago
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆77Updated 9 months ago
• bpucla / latent-space-EBM-prior
  ☆36Updated 4 years ago
• Gabe-YHLee / NRAE-public
  ☆32Updated 2 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆74Updated 3 years ago
• yilundu / comet
  [NeurIPS 2021] Code for Unsupervised Learning of Compositional Energy Concepts
  ☆61Updated 2 years ago