StephanLorenzen / MajorityVoteBounds
A framework for majority vote classifiers allowing for computation of PAC Bayesian risk bounds.
☆13Updated last year
Related projects ⓘ
Alternatives and complementary repositories for MajorityVoteBounds
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆76Updated 8 months ago
- PAC-Bayes with Backprop - Tighter risk certificates for neural networks☆24Updated 3 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 2 years ago
- Generative Forests in Python☆32Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆37Updated last year
- ☆15Updated 2 years ago
- Python implementation of projection losses.☆25Updated 4 years ago
- ☆13Updated last year
- csl: PyTorch-based Constrained Learning☆12Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- This repository contains the Python code to reproduce all the figures and experiments presented in the paper: Masegosa, Andrés. R., Learn…☆9Updated last year
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆57Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- #UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning☆12Updated 2 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆21Updated 3 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- ☆52Updated 3 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- SGD with large step sizes learns sparse features [ICML 2023]☆32Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆80Updated 4 months ago
- Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference☆12Updated 4 years ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆15Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 2 years ago
- Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights☆26Updated 3 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- Inference on non-linear dynamical systems written in JAX☆12Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆43Updated last year
- Influence Estimation for Gradient-Boosted Decision Trees☆26Updated 5 months ago