aleximmer / heteroscedastic-nnLinks
Code for "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks" (NeurIPS 2023)
☆21Updated 8 months ago
Alternatives and similar repositories for heteroscedastic-nn
Users that are interested in heteroscedastic-nn are comparing it to the libraries listed below
Sorting:
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆139Updated 3 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆49Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- ☆155Updated 3 years ago
- Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"☆22Updated 2 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- A hello world Bayesian Neural Network project on MNIST☆49Updated 3 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆143Updated 2 years ago
- Official repository for "Estimating Epistemic and Aleatoric Uncertainty with a Single Model"☆23Updated last year
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆552Updated last year
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆46Updated 3 years ago
- Experiments for Neural Flows paper☆99Updated 4 years ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆81Updated 7 months ago
- [ICLR 2024] Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data☆61Updated 3 months ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆35Updated 3 months ago
- Bayesian neural networks via MCMC: tutorial☆60Updated last year
- ☆239Updated 5 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 5 years ago
- ODE2VAE: Deep generative second order ODEs with Bayesian neural networks☆130Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆78Updated 2 months ago
- ☆109Updated 4 years ago
- Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series☆119Updated 2 years ago
- Continual Gaussian Processes☆31Updated 2 years ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆460Updated 3 months ago