This repository contains the official code of the paper NRGBoost: Energy-Based Generative Boosted Trees (ICLR 2025).
Online Multi-Class LPBoost
code for Variational Boosting: Iteratively Refining Posterior Approximations
This project is a cleaned up version of our PAMI submission "Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly" in tensorflow. It extends our original ICCV version with an adversarial auxiliary loss during training, which improves results. you are planning to use this…
Las características principales de mop/bier son: Gradient Boosting Research.
Las alternativas de código abierto para mop/bier incluyen: ajoo/nrgboost — This repository contains the official code of the paper NRGBoost: Energy-Based Generative Boosted Trees (ICLR 2025). amirsaffari/online-multiclass-lpboost — Online Multi-Class LPBoost. andymiller/vboost — code for Variational Boosting: Iteratively Refining Posterior Approximations. anitan0925/resfgb — Remark: The code is updated from the ICML version. The ICML version corresponds to a commit on May 25, 2018. arogozhnikov/infiniteboost — Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov,… aciditeam/acidano.
