StephanLorenzen / MajorityVoteBounds
A framework for majority vote classifiers allowing for computation of PAC Bayesian risk bounds.
☆13Updated 2 years ago
Alternatives and similar repositories for MajorityVoteBounds:
Users that are interested in MajorityVoteBounds are comparing it to the libraries listed below
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- ☆15Updated 2 years ago
- PAC-Bayes with Backprop - Tighter risk certificates for neural networks☆24Updated 3 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆16Updated 3 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated 11 months ago
- SGD with large step sizes learns sparse features [ICML 2023]☆32Updated last year
- Influence Estimation for Gradient-Boosted Decision Trees☆26Updated 8 months ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- This repository contains PyTorch implementations of various random feature maps for dot product kernels.☆19Updated 7 months ago
- Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights☆27Updated 4 years ago
- csl: PyTorch-based Constrained Learning☆12Updated 2 years ago
- Tools for robustness evaluation in interpretability methods☆10Updated 3 years ago
- ☆35Updated last year
- ☆20Updated 4 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)☆28Updated 4 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆41Updated last year
- ☆42Updated 6 years ago
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆24Updated 11 months ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 9 months ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆21Updated 4 years ago
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆58Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 3 years ago
- ☆9Updated 2 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