Alternatives and similar repositories for SDE-Net

Users that are interested in SDE-Net are comparing it to the libraries listed below

• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated last year
• mhw32 / meta-inference-public
  A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)
  ☆14Updated 5 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago
• Shen-Lab / Bayesian-L2O
  [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…
  ☆14Updated 3 years ago
• thudzj / NeuralEigenFunction
  ☆17Updated 3 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆60Updated last year
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 5 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆44Updated last year
• ChengzijunAixiaoli / PPMM
  Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]
  ☆15Updated 4 years ago
• federicobergamin / Variational-Inference-with-Normalizing-Flows
  Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch
  ☆23Updated 5 years ago
• mstaib / mmd-dro-code
  Accompanying code for our NeurIPS 2019 paper
  ☆12Updated 6 years ago
• Lingkai-Kong / SDE-Net
  Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
  ☆116Updated 5 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 6 years ago
• tdmeeste / TimeAwareRNN
  Code used for the AAAI 2020 paper "System Identification with Time-Aware Neural Sequence Models"
  ☆17Updated 6 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆49Updated 5 years ago
• clear-nus / NCDSSM
  PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…
  ☆25Updated 2 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆47Updated 2 years ago
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆29Updated 7 months ago
• chenw20 / SGPA
  Example code of Sparse Gaussian Process Attention (ICLR 2023)
  ☆26Updated 2 months ago
• StanfordASL / moca
  ☆32Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago
• yixinwang / representation-causal-public
  ☆45Updated 3 years ago
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 3 years ago