lxcnju / NeuralProcessLinks
PyTorch for Neural Process in ICML 2018
☆20Updated 6 years ago
Alternatives and similar repositories for NeuralProcess
Users that are interested in NeuralProcess are comparing it to the libraries listed below
Sorting:
- Code for paper Stochastic Deep Gaussian Processes over Graphs☆21Updated 4 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆117Updated 5 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆65Updated 3 years ago
- demonstration of the information bottleneck theory for deep learning☆69Updated 8 years ago
- Repository for ICLR 2023 work, "Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting"☆31Updated last year
- An encoder-decoder framework for learning from incomplete data☆45Updated 2 years ago
- Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"☆50Updated 4 years ago
- ☆26Updated 4 years ago
- implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)☆100Updated 10 months ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆64Updated 5 years ago
- A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).☆162Updated 6 years ago
- ☆97Updated 2 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 7 years ago
- implementations sde-net☆14Updated 5 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 5 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆41Updated last year
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆61Updated last year
- ☆97Updated last year
- Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …☆77Updated 3 years ago
- This repository is the implementation of Deep Dirichlet Process Mixture Models (UAI 2022)☆15Updated 3 years ago
- Neural Dynamics on Complex Networks☆55Updated 5 years ago
- Official code of GIND (Optimization-Induced Graph Implicit Nonlinear Diffusion)☆18Updated 3 years ago
- Graph Imputation Neural Network☆79Updated 5 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- Discovering directional relations via minimum predictive information regularization☆23Updated 6 years ago
- Uncertainty Aware Semi-Supervised Learning on Graph Data☆40Updated 4 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated last year
- Python package for graph-based clustering and semi-supervised learning☆101Updated 2 weeks ago
- A PyTorch reimplementation of MAML, replicating some of the experiments from the paper.☆44Updated 7 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago