Custom component to calculate estimated power consumption of lights and other appliances

This is a library to allow communicating to a Midea appliance via the Midea cloud.

ASCII generator (image to text, image to image, video to video)

Linux 内核实验（Linux kernel labs）中文翻译

learning basic computer knowledge and fundamental philosophy.

搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

Meta Learning with Implicit Gradients (iMAML)

Repo to accompany paper on Meta Learning with Implicit Gradients (NeurIPS 2019)

[ECAI 2024] A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization

Benchmark for bi-level optimization solvers

Bi-level Optimization for Advanced Deep Learning

Collection of algorithms to learn loss and reward functions via gradient-based bi-level optimization.

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

code implementation for 'Bi-level Actor-Critic for Multi-agent Coordination'(AAAI2020)

Reinforcement Learning based TCP congestion control

TCP congestion control using ns3-gym setup for DQN reinforcement learning.

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

An asynchronous RL platform for congestion control in QUIC transport protocol. https://arxiv.org/abs/1910.04054.

Augmented Traffic Control: A tool to simulate network conditions

A Simple Traffic Generator for Network Experiments

An interface to program any congestion control protocol for an unreliable connection based protocol sent over UDP. It comes with a clean TrafficGenerator interface that can generate traffic for eac…

Smart PVR for newsgroup and bittorrent users.

Code of the paper: Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value Function

Implementation of Meta-RL A3C algorithm

A collection of Meta-Reinforcement Learning algorithms in PyTorch

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.