Popular GitHub Repositories for Thompson Sampling

LightSeq: A High Performance Library for Sequence Processing and Generation

A procedural Blender pipeline for photorealistic training image generation

Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)

:dart: Task-oriented embedding tuning for BERT, CLIP, etc.

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

Boltzmann Machines in TensorFlow with examples

基于Pytorch和torchtext的自然语言处理深度学习框架。

Pool-based active learning in Python

PyTorch Implementation for Deep Metric Learning Pipelines

Simple and readable code for training and sampling from diffusion models

A comprehensive code for AI & Robotics.

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

? Research Framework for Single and Multi-Players ? Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-player (MusicalChair, MEGA, rhoRand, MCTop/RandTopM etc).. Available on PyPI: https://pypi.org/project/SMPyBandits/ and documentation on

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

Official Repository of the paper "Trajectory Consistency Distillation"

Synthetic Minority Over-Sampling Technique for Regression

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

The Noise Contrastive Estimation for softmax output written in Pytorch

Skipgram Negative Sampling implemented in PyTorch

6 nodes for ComfyUI that allows for more control and flexibility over noise to do e.g. variations or "un-sampling"