activatedgeek / understanding-bayesian-classification
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification
☆21Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for understanding-bayesian-classification
- Bayesian active learning with EPIG data acquisition☆25Updated 6 months ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 2 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆22Updated last year
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated last year
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆38Updated last year
- Dynamic causal Bayesian optimisation☆34Updated last year
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆22Updated 8 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆15Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 2 years ago
- Dataset repository for the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jo…☆24Updated 2 weeks ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆80Updated 7 months ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆64Updated this week
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆10Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆18Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆86Updated 4 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆21Updated 4 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆25Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆56Updated 2 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆10Updated 10 months ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆47Updated 6 months ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆54Updated 8 months ago