🌾 OAT: A research-friendly framework for LLM online alignment, including reinforcement learning, preference learning, etc.

Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)

👤 Multi-Armed Bandit Algorithms Library (MAB) 👮

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.

Thompson Sampling Tutorial

Python library for Multi-Armed Bandits

All codes, both created and optimized for best results from the SuperDataScience Course

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Stop overpaying to run your agents. Kalibr routes every request to lower-cost model and tool paths without degrading performance.

Bandit algorithms

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Study of the paper 'Neural Thompson Sampling' published in October 2020

🧠 Windows GUI с ИИ-оркестратором (Thompson Sampling + генетическая эволюция) для zapret-профилей Flowseal. Самообучаемый подбор стратегий под вашу сеть.

Offline evaluation of multi-armed bandit algorithms

Agent governance for ThumbGate: 👍/👎 become Pre-Action Checks that block repeat mistakes before code, money, or customer systems change.

A Julia Package for providing Multi Armed Bandit Experiments

Bayesian Optimization for Categorical and Continuous Inputs

The official code release for "Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning", ICLR 2025

A curated list on papers about combinatorial multi-armed bandit problems.