TF-Speech-Recognition-Challenge-SolutionSource code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.
Stars: ✭ 58 (-64.2%)
pgdlWinning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning
Stars: ✭ 36 (-77.78%)
FOCAL-ICLRCode for FOCAL Paper Published at ICLR 2021
Stars: ✭ 35 (-78.4%)
yarllCombining deep learning and reinforcement learning.
Stars: ✭ 84 (-48.15%)
pomdp-pyA framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
Stars: ✭ 131 (-19.14%)
Fruit-APIA Universal Deep Reinforcement Learning Framework
Stars: ✭ 61 (-62.35%)
DARNNA Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
Stars: ✭ 90 (-44.44%)
reinforcement learning ppo rndDeep Reinforcement Learning by using Proximal Policy Optimization and Random Network Distillation in Tensorflow 2 and Pytorch with some explanation
Stars: ✭ 33 (-79.63%)
pyradoxState of the Art Neural Networks for Deep Learning
Stars: ✭ 61 (-62.35%)
Pytorch A2c Ppo Acktr GailPyTorch 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).
Stars: ✭ 2,632 (+1524.69%)
action-branching-agents(AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning
Stars: ✭ 91 (-43.83%)
SS-ReplanOnline Replanning in Belief Space for Partially Observable Task and Motion Problems
Stars: ✭ 43 (-73.46%)
DRL in CVA course on Deep Reinforcement Learning in Computer Vision. Visit Website:
Stars: ✭ 59 (-63.58%)
LearningxDeep & Classical Reinforcement Learning + Machine Learning Examples in Python
Stars: ✭ 241 (+48.77%)
svae cf[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering
Stars: ✭ 38 (-76.54%)
Pytorch-PCGradPytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
Stars: ✭ 179 (+10.49%)
scala-rlFunctional Reinforcement Learning in Scala.
Stars: ✭ 26 (-83.95%)
Pytorch DrlPyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Stars: ✭ 233 (+43.83%)
Deep Rl Tradingplaying idealized trading games with deep reinforcement learning
Stars: ✭ 228 (+40.74%)
rnn benchmarksRNN benchmarks of pytorch, tensorflow and theano
Stars: ✭ 85 (-47.53%)
GamA PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
Stars: ✭ 227 (+40.12%)
TrixiManage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.
Stars: ✭ 211 (+30.25%)
PH5Library of PH5 clients, apis, and utilities
Stars: ✭ 14 (-91.36%)
Chanlun文件 笔和线段的一种划分.py,只需要把k线high,low数据输入,就能自动实现笔,线段,中枢,买卖点,走势类型的划分了。可以把sh.csv 作为输入文件。个人简历见.pdf。时间的力量。有人说择时很困难,有人说选股很容易,有人说统计套利需要的IT配套设施很重要。还有人说系统有不可测原理。众说纷纭。分布式的系统,当你的影响可以被忽略,你才能实现,Jiang主席所谓之,闷声发大财。
Stars: ✭ 206 (+27.16%)
DeepCubeACode for DeepCubeA, a Deep Reinforcement Learning algorithm that can learn to solve the Rubik's cube.
Stars: ✭ 92 (-43.21%)
PapersSummaries of machine learning papers
Stars: ✭ 2,362 (+1358.02%)
awesome-rlAwesome RL: Papers, Books, Codes, Benchmarks
Stars: ✭ 105 (-35.19%)
Human-Activity-RecognitionHuman activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
Stars: ✭ 16 (-90.12%)
Atari Model ZooA binary release of trained deep reinforcement learning models trained in the Atari machine learning benchmark, and a software release that enables easy visualization and analysis of models, and comparison across training algorithms.
Stars: ✭ 198 (+22.22%)
deep rl acrobotTensorFlow A2C to solve Acrobot, with synchronized parallel environments
Stars: ✭ 32 (-80.25%)
Drl4recsysCourses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems
Stars: ✭ 196 (+20.99%)
ACTAlternative approach for Adaptive Computation Time in TensorFlow
Stars: ✭ 16 (-90.12%)
Awesome Deep RlA curated list of awesome Deep Reinforcement Learning resources.
Stars: ✭ 193 (+19.14%)
Naf Tensorflow"Continuous Deep Q-Learning with Model-based Acceleration" in TensorFlow
Stars: ✭ 192 (+18.52%)
RL courseThe page of the Ural Federal University course "Reinforcement Learning and Neural Networks"
Stars: ✭ 23 (-85.8%)
Pytorch sacPyTorch implementation of Soft Actor-Critic (SAC)
Stars: ✭ 174 (+7.41%)
Machine Learning Is All You Need🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
Stars: ✭ 173 (+6.79%)
alphastoneUsing self-play, MCTS, and a deep neural network to create a hearthstone ai player
Stars: ✭ 24 (-85.19%)
DrlRepository for codes of 'Deep Reinforcement Learning'
Stars: ✭ 172 (+6.17%)
Noisynet A3cNoisy Networks for Exploration
Stars: ✭ 171 (+5.56%)
good robot"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer
Stars: ✭ 84 (-48.15%)
ml course"Learning Machine Learning" Course, Bogotá, Colombia 2019 #LML2019
Stars: ✭ 22 (-86.42%)
Deep Reinforcement Learning Algorithms31 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
Stars: ✭ 167 (+3.09%)