YannDubs / Neural-Process-FamilyLinks
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
☆225Updated last year
Alternatives and similar repositories for Neural-Process-Family
Users that are interested in Neural-Process-Family are comparing it to the libraries listed below
Sorting:
- Implementation of the Convolutional Conditional Neural Process☆125Updated 4 years ago
- Pytorch implementation of Neural Processes for functions and images☆233Updated 3 years ago
- A framework for composing Neural Processes in Python☆85Updated 8 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- ☆152Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆457Updated last year
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆230Updated 10 months ago
- ☆243Updated 2 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆74Updated 3 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆62Updated 4 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆123Updated 8 months ago
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆147Updated last month
- Masked Autoregressive Flow☆216Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆69Updated 3 months ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆97Updated 5 months ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆448Updated last week
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.☆280Updated last year
- Manifold-learning flows (ℳ-flows)☆230Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆118Updated 2 years ago
- Laplace approximations for Deep Learning.☆517Updated 4 months ago
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Experiments for Neural Flows paper☆97Updated 3 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆287Updated 4 years ago
- Code for "Latent ODEs for Irregularly-Sampled Time Series" paper☆561Updated 4 years ago