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baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

boostersdrc

Second place solution for Digital Reputation Challenge on boosters.pro

cartpolerl

case-212

Открытое письмо специалистов IT-индустрии в защиту фигурантов «московского дела»

explorer

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

liir

Learning Individual Intrinsic Reward in MARL

ml

ML algorithms

mmp_prac_2017

Этот репозиторий содержит материалы к курсу <<Практикум на ЭВМ,

mmp_prac_spring_2018

nabladft

nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset

ppo-moldynamics

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

practical-rl

Based on https://github.com/yandexdataschool/Practical_RL

rlax

rlfamily_cv

Code for the Paper Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods

sd3

soft-actor-critic

Modified versions of the SAC algorithm from spinningup for discrete action spaces and image observations.

spinningup

An educational resource to help anyone learn deep reinforcement learning.

survival-analisys-with-anomaly-detection

New method of Survival analysis for systems, described with multivariate timeseries, based on anomaly detector.

tabsyn

Official Implementations of "Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space""

top

Implementation of Tactical Optimistic and Pessimistic value estimation

toxic-comment-classification

See https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge for information on challenge.