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Code examples that accompany various MDN DOM and Web API documentation pages
This sample demonstrates how you can publish your Progressive Web App (PWA) on Google Play Store with Trusted Web Activities (TWA), and use Digital Goods API and Payment Request API to receive paym…
supsucc / neuron_poker
Forked from dickreuter/neuron_pokerTexas holdem OpenAi gym poker environment with reinforcement learning based on keras-rl. Includes virtual rendering and montecarlo for equity calculation.
supsucc / langchain
Forked from langchain-ai/langchain🦜🔗 Build context-aware reasoning applications
supsucc / gpugt
Forked from uoftcprg/gpugtGPU parallelizable implementation of counterfactual regret minimization
supsucc / open_spiel
Forked from google-deepmind/open_spielOpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
supsucc / robopoker
Forked from krukah/robopokerPlay, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.
A Very Simple Poker Playing Bot using OpenCV and Tesseract for Computer Vision and a Simple Decision Tree base AI
Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.
Texas holdem OpenAi gym poker environment with reinforcement learning based on keras-rl. Includes virtual rendering and montecarlo for equity calculation.
Texas hold'em poker engine
Poker bot using hand strength calculation, pre-flop simulation and opponent modeling
CausalLift: Python package for causality-based Uplift Modeling in real-world business
➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
Code for "Counterfactual Fairness" (NIPS2017)
Counterfactual regret minimization algorithm for Kuhn poker
Code for paper "Personalized Counterfactual Fairness in Recommendation" (a.k.a. "Towards Personalized Fairness based on Causal Notion")
A poker AI for NL Texas Holdem trained using Monte-Carlo Counterfactual Regret Minimization.
Implemented the CFR+ and PureCFR algorithms in Python to find the optimal strategies to 2-player extensive-form games, which was also used in Libratus, the best poker AI in the world
A NLTH Poker Agent using Counterfactual Regret Minimization
PyTorch implementation of Foerster, Jakob N., et al. "Counterfactual multi-agent policy gradients."
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.