Update README.md

Author: krzjoa

README.md

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 * [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3) - A set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines.
 * [RLlib](https://ray.readthedocs.io/en/latest/rllib.html) - Scalable Reinforcement Learning.
 * [Acme](https://github.com/google-deepmind/acme) - A library of reinforcement learning components and agents.
-* [Catalyst-RL](https://github.com/catalyst-team/catalyst-rl) - PyTorch framework for RL research.
+* [Catalyst-RL](https://github.com/catalyst-team/catalyst-rl) - PyTorch framework for RL research. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
 * [d3rlpy](https://github.com/takuseno/d3rlpy) - An offline deep reinforcement learning library.
-* [Tianshou](https://github.com/thu-ml/tianshou/#comprehensive-functionality) - An elegant PyTorch deep reinforcement learning library.
-* [TF-Agents](https://github.com/tensorflow/agents) - A library for Reinforcement Learning in TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
-* [TensorForce](https://github.com/reinforceio/tensorforce) - A TensorFlow library for applied reinforcement learning. <img height="20" src="img/tf_big2.png" alt="sklearn">
+* [Tianshou](https://github.com/thu-ml/tianshou/#comprehensive-functionality) - An elegant PyTorch deep reinforcement learning library. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+* [TF-Agents](https://github.com/tensorflow/agents) - A library for Reinforcement Learning in TensorFlow. <img height="20" src="img/tf_big2.png" alt="TensorFlow">
+* [TensorForce](https://github.com/reinforceio/tensorforce) - A TensorFlow library for applied reinforcement learning. <img height="20" src="img/tf_big2.png" alt="TensorFlow">
 * [TRFL](https://github.com/deepmind/trfl) - TensorFlow Reinforcement Learning. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [Dopamine](https://github.com/google/dopamine) - A research framework for fast prototyping of reinforcement learning algorithms.
 * [keras-rl](https://github.com/keras-rl/keras-rl) - Deep Reinforcement Learning for Keras. <img height="20" src="img/keras_big.png" alt="Keras compatible">
 * [garage](https://github.com/rlworkgroup/garage) - A toolkit for reproducible reinforcement learning research.
 * [Horizon](https://github.com/facebookresearch/Horizon) - A platform for Applied Reinforcement Learning.
+* [rlpyt](https://github.com/astooke/rlpyt) - Reinforcement Learning in PyTorch. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+* [cleanrl](https://github.com/vwxyzjn/cleanrl) - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG).
+* [Machin](https://github.com/iffiX/machin) - A reinforcement library designed for pytorch. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+* [SKRL](https://github.com/Toni-SM/skrl) - Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Isaac Orbit and Omniverse Isaac Gym. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
 
 ## Graph Machine Learning
 * [pytorch_geometric](https://github.com/rusty1s/pytorch_geometric) - Geometric Deep Learning Extension Library for PyTorch. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
 * [pytorch_geometric_temporal](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) - Temporal Extension Library for PyTorch Geometric. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
-* [dgl](https://github.com/dmlc/dgl) - Python package built to ease deep learning on graph, on top of existing DL frameworks.
+* [PyTorch Geometric Signed Directed](https://github.com/SherylHYX/pytorch_geometric_signed_directed) - A signed/directed graph neural network extension library for PyTorch Geometric. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+* [dgl](https://github.com/dmlc/dgl) - Python package built to ease deep learning on graph, on top of existing DL frameworks. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible"> <img height="20" src="img/tf_big2.png" alt="TensorFlow"> <img height="20" src="img/mxnet_big.png" alt="MXNet based">
 * [Spektral](https://github.com/danielegrattarola/spektral) - Deep learning on graphs. <img height="20" src="img/keras_big.png" alt="Keras compatible">
+* [StellarGraph](https://github.com/stellargraph/stellargraph) - Machine Learning on Graphs. <img height="20" src="img/tf_big2.png" alt="TensorFlow"> <img height="20" src="img/keras_big.png" alt="Keras compatible">
+* [Graph Nets](https://github.com/google-deepmind/graph_nets) - Build Graph Nets in Tensorflow. <img height="20" src="img/tf_big2.png" alt="TensorFlow">
+* [TensorFlow GNN](https://github.com/tensorflow/gnn) - A library to build Graph Neural Networks on the TensorFlow platform. <img height="20" src="img/tf_big2.png" alt="TensorFlow">
+* [Auto Graph Learning](https://github.com/THUMNLab/AutoGL) -An autoML framework & toolkit for machine learning on graphs.
+* [PyTorch-BigGraph](https://github.com/facebookresearch/PyTorch-BigGraph) - Generate embeddings from large-scale graph-structured data. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
+* [Auto Graph Learning](https://github.com/THUMNLab/AutoGL) - An autoML framework & toolkit for machine learning on graphs.
 * [Karate Club](https://github.com/benedekrozemberczki/karateclub) - An unsupervised machine learning library for graph-structured data.
 * [Little Ball of Fur](https://github.com/benedekrozemberczki/littleballoffur) - A library for sampling graph structured data.
+* [GreatX](https://github.com/EdisonLeeeee/GreatX) - A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG). <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
 
 ## Probabilistic Graphical Models
 * [pomegranate](https://github.com/jmschrei/pomegranate) - Probabilistic and graphical models for Python. <img height="20" src="img/gpu_big.png" alt="GPU accelerated">