Popular GitHub Repositories for Bregman Divergence

Boltzmann Machines in TensorFlow with examples

一个 Python 库，用于计算两个输入之间的梅尔倒谱距离（梅尔倒谱失真，MCD）。此实现基于 Robert F. Kubichek 在“用于客观语音质量评估的梅尔倒谱距离度量”中提出的方法。

一个用于计算两个输入之间梅尔倒谱距离 (Mel-Cepstral Distortion, MCD) 的 Python 库。此实现基于 Robert F. Kubichek 在“用于客观语音质量评估的梅尔倒谱距离度量”中提出的方法。

PyTorch code for FLD (Feature Likelihood Divergence), FID, KID, Precision, Recall, etc. using DINOv2, InceptionV3, CLIP, etc.

A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"

? Energy-Based Modeling library for PyTorch, offering tools for sampling, inference, and learning in complex distributions.

Repository for "Blending Data-Driven Priors in Dynamic Games" - RSS 2024

Source code for ECML-PKDD (2020) paper: FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning

Maximum Mean Discrepancy (MMD), Kernel Stein Discrepancy (KSD), and Fisher Divergence

Experiments of the three PPO-Algorithms (PPO, clipped PPO, PPO with KL-penalty) proposed by John Schulman et al. on the 'Cartpole-v1' environment.

Python implementation of Restricted Boltzmann Machine (RBM). And an example on MNIST dataset.

This repository contains the lab work for Coursera course on "Generative AI with Large Language Models".

[WNGT(2019)] On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation

A methodology designed to validate the statistical similarity of synthetic data generated by GAN models. The metrics contain Auto-encoder, PCA, t-SNE, KL-divergence, Clustering, and Cosine Similarity.

This is the official repository of L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning github

Experiments of divergence functions for DPO, RLHF

Python implementation of Bregman Hard Clustering and Bregman Soft Clustering as a scikit-learn module.

The ShadBot package has the ability to conduct trade online, perform backtests for offline trades, and review and analyze them, as well as optimize trades. Also, this package has the ability to optimize using artificial intelligence and predict future price values using machine learning algorithms

Basic GANs with variety of loss functions as an exercise for my Thesis with Prof. Randy Paffenroth. KL, Reverse-KL, JS and Wasserstein GAN.

Coordinate ascent mean-field variational inference (CAVI) using the evidence lower bound (ELBO) to iteratively perform the optimal variational factor distribution parameter updates for clustering.