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🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
speech enhancement\speech seperation\sound source localization
Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)
A curated list of different papers and datasets in various areas of audio-visual processing
Curated list of python software and packages related to scientific research in audio
A curated list about Audio Visualization.
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
A comprehensive list of awesome contrastive self-supervised learning papers.
A collection of important graph embedding, classification and representation learning papers with implementations.
Paper Lists for Graph Neural Networks
An educational resource to help anyone learn deep reinforcement learning.
PyTorch implementations of deep reinforcement learning algorithms and environments
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
A starter agent that can solve a number of universe environments.
Simple Online Realtime Tracking with a Deep Association Metric
Modularized Implementation of Deep RL Algorithms in PyTorch
Extensible, parallel implementations of t-SNE
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
The newest reading list for representation learning