AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
☆89Aug 31, 2020Updated 6 years ago
Alternatives and similar repositories for Bayesian_NN_Ensembles
Users that are interested in Bayesian_NN_Ensembles are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- UAI paper 'Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions'☆11Jun 26, 2019Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Apr 8, 2020Updated 6 years ago
- ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'☆94Apr 9, 2020Updated 6 years ago
- Repository of NeurIPS 2019 paper "Calibration tests in multi-class classification: A unifying framework"☆17May 6, 2021Updated 5 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆26Oct 28, 2021Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019☆13Apr 25, 2019Updated 7 years ago
- Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Published at Uncertainty in AI (UAI) 2020.☆11Aug 31, 2020Updated 6 years ago
- ☆13Mar 16, 2019Updated 7 years ago
- Finding the conditional distributions of a Gaussian Mixture Model☆13Nov 10, 2019Updated 6 years ago
- ☆53May 4, 2018Updated 8 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,975Oct 20, 2023Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Aug 14, 2018Updated 8 years ago
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆30Nov 28, 2022Updated 3 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆162Jul 23, 2022Updated 4 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- ☆13Nov 30, 2023Updated 2 years ago
- ☆69May 26, 2018Updated 8 years ago
- Uncertainty interpretations of the neural network☆32May 3, 2018Updated 8 years ago
- Repository for conditional transport☆15Jan 12, 2022Updated 4 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆477Jul 6, 2023Updated 3 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆150Jun 2, 2023Updated 3 years ago
- This repo contains active learning query strategies as introduced in our GCPR 2013 paper.☆12Aug 12, 2013Updated 13 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆581Feb 26, 2022Updated 4 years ago
- Resources for the paper titled "Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts".…☆20Jul 12, 2023Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆248Dec 3, 2019Updated 6 years ago
- ☆21Mar 5, 2021Updated 5 years ago
- An HMC/NUTS implementation in Aesara☆31Jun 22, 2023Updated 3 years ago
- Variational Reinforcement Learning☆18Jul 25, 2024Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆105Oct 10, 2018Updated 8 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆377Jan 28, 2017Updated 9 years ago
- ☆13Oct 12, 2020Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆39Dec 15, 2017Updated 8 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Dec 19, 2018Updated 7 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- This repository contains an official implementation of LPBNN.☆38Jun 28, 2023Updated 3 years ago
- Attentive Sequential Model Based on Graph Neural Network for Next POI Recommendation☆11Sep 6, 2022Updated 4 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2020☆33Dec 15, 2022Updated 3 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Dec 20, 2023Updated 2 years ago
- IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation☆40Jul 18, 2025Updated last year
- Random Forests for Conditional Density Estimation☆44Jun 10, 2021Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆46Jul 30, 2024Updated 2 years ago