#other #computer_vision #cvpr #cvpr2020 #deep_learning #image_processing #image_segmentation #machine_learning #object_detection #paper #visual_tracking

https://github.com/amusi/CVPR2020-Code

#python #alae #autoencoder #celeba #celeba_hq #computer_vision #cvpr2020 #deep_learning #face_generation #ffhq #gan #generative_adversarial_network #generative_model #machine_learning #neural_network #paper #paper_implementations #pytorch #pytorch_implementation #stylegan

https://github.com/podgorskiy/ALAE

#other #artificial_intelligence #data_mining #data_science #deep_learning #game_theory #hardware #learning_theory #literature #machine_learning #machine_learning_algorithms #neural_network #paper #pattern_recognition #reinforcement_learning #silicon #statistical_learning #statistics

https://github.com/tirthajyoti/Papers-Literature-ML-DL-RL-AI

#python #audio #generative_model #music #paper #pytorch #transformer #vq_vae

https://github.com/openai/jukebox

#other #deep_learning #machine_learning #natural_language_processing #neural_networks #paper_list #surveys

https://github.com/NiuTrans/ABigSurvey

#shell #bukkit #burritos #craftbukkit #hacktoberfest #java #minecraft #minecraft_api #minecraft_performance #minecraft_server #paper_fork

https://github.com/Spottedleaf/Tuinity

#python #paper #dataset

https://github.com/uzh-rpg/rpg_timelens

#other #deep_learning #paper #reading_list

https://github.com/mli/paper-reading

#other #2021 #ai #artificial_intelligence #artificialintelligence #computer_science #computer_vision #deep_learning #innovation #machine_learning #machinelearning #paper #papers #python #research #research_paper #sota #sota_technique #state_of_art #state_of_the_art #technology

https://github.com/louisfb01/best_AI_papers_2021

#python #attention #cbam #excitation_networks #linear_layers #paper #pytorch #squeeze #visual_tasks

https://github.com/xmu-xiaoma666/External-Attention-pytorch

#other #2022 #ai #artificial_intelligence #computer_science #computer_vision #deep_learning #innovation #machine_learning #machinelearning #neural_network #paper #papers #python #sota #state_of_art #state_of_the_art #technology

https://github.com/louisfb01/best_AI_papers_2022

#python #algorithmic_trading #algotrading #alpha #arbitrage_bot #awesome #awesome_list #book #finance #futures #futures_historical_data #futures_market #futuresmarkets #paper #quant #quantitative_finance #quantitative_trading #trading_algorithms #trading_bot #trading_strategies

https://github.com/edarchimbaud/awesome-systematic-trading

#java #bukkit #bukkit_plugin #discord #essential #essentials #essentials_chat #essentials_core #essentials_spawn #essentialsx #hacktoberfest #minecraft #minecraft_oss #minecraft_plugin #minecraft_server #moss_discord_community #paper #spigot #spigot_plugin

https://github.com/EssentialsX/Essentials

#python #deep_learning #domain_adaptation #domain_adaption #domain_generalization #few_shot #few_shot_learning #generalization #machine_learning #meta_learning #paper #papers #representation_learning #self_supervised_learning #style_transfer #survey #theory #transfer_learning #transferlearning #tutorial_code #unsupervised_learning

https://github.com/jindongwang/transferlearning

#java #bukkit #hacktoberfest #java #minecraft #minecraft_api #minecraft_performance #minecraft_server #paper #paper_api #papermc #tacos

Paper is a high-performance Minecraft server that fixes many gameplay and mechanics issues. It's easy to use: just download the Paperclip jar file and run it on your server. For server admins, there are detailed guides and documentation available. Plugin developers can access API patches and javadocs to create compatible plugins. You can also compile the jar from source if you need custom changes. Supporting Paper through donations helps maintain its infrastructure and ensures continuous improvements. This makes your Minecraft experience smoother and more enjoyable.

https://github.com/PaperMC/Paper

#python #algorithmic_trading #auto_quant #deep_learning #finance #fintech #investment #machine_learning #paper #platform #python #quant #quant_dataset #quant_models #quantitative_finance #quantitative_trading #research #research_paper #stock_data

Qlib is an open-source platform for quantitative investment that uses AI technologies. It supports various machine learning models and helps in finding valuable signals in financial data, adapting to market dynamics, and optimizing trading strategies. Here are the key benefits Qlib introduces RD-Agent, a tool that automates factor mining and model optimization, making it easier to develop quant investment strategies.
- **Diverse Machine Learning Models** It covers the entire chain of quantitative investment, including data processing, model training, backtesting, and order execution.
- **Customizable Workflows** Qlib's data server is optimized for performance, allowing fast data processing and retrieval, which is crucial for real-time trading decisions.

Overall, Qlib simplifies the process of building and optimizing quant investment strategies, making it a powerful tool for researchers and investors.

https://github.com/microsoft/qlib