automl / TransformersCanDoBayesianInferenceLinks
Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
☆233Updated 11 months ago
Alternatives and similar repositories for TransformersCanDoBayesianInference
Users that are interested in TransformersCanDoBayesianInference are comparing it to the libraries listed below
Sorting:
- Our maintained PFN repository. Come here to train SOTA PFNs.☆106Updated 2 weeks ago
- Simple (and cheap!) neural network uncertainty estimation☆70Updated 4 months ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆226Updated last year
- ☆154Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 4 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆86Updated last year
- Conformalized Quantile Regression☆286Updated 3 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆68Updated 7 months ago
- ☆245Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆34Updated 2 weeks ago
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- ☆51Updated last year
- Laplace approximations for Deep Learning.☆517Updated 5 months ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆34Updated last month
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆458Updated last year
- Regression datasets from the UCI repository with standardized test-train splits.☆48Updated 3 years ago
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆52Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆48Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- CausalPFN: Amortized Causal Effect Estimation via In-Context Learning☆55Updated last month
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆622Updated 5 months ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆90Updated 3 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆69Updated 10 months ago