BlackHC / BatchBALDLinks
Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.
☆241Updated last year
Alternatives and similar repositories for BatchBALD
Users that are interested in BatchBALD are comparing it to the libraries listed below
Sorting:
- Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For…☆203Updated 5 years ago
- Reusable BatchBALD implementation☆79Updated last year
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆468Updated 2 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Variational Adversarial Active Learning (ICCV 2019)☆231Updated 2 years ago
- Calibration of Convolutional Neural Networks☆166Updated 2 years ago
- Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach☆272Updated 6 years ago
- An implementation of the BADGE batch active learning algorithm.☆207Updated last year
- Awesome Active Learning Paper List☆142Updated last year
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- ☆40Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- ☆415Updated 3 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆160Updated last year
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 years ago
- code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018☆67Updated 3 years ago
- Code for Deep Bayesian Active Learning (ICML 2017)☆112Updated 7 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆150Updated 2 years ago
- This project contains code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017☆88Updated 3 years ago
- Self-Supervised Learning for OOD Detection (NeurIPS 2019)☆267Updated 4 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Updated 5 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- A simple and effective method for detecting out-of-distribution images in neural networks.☆536Updated 3 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆176Updated last year
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆459Updated 6 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago