• Horizon

  • Referenced in 6 articles [sw31157]
  • Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform. In this paper we present Horizon ... Facebook’s open source applied reinforcement learning (RL) platform. Horizon ... platform designed to solve industry applied RL problems where datasets are large (millions to billions ... showcase and describe real examples where reinforcement learning models trained with Horizon significantly outperformed...
  • DARTS

  • Referenced in 14 articles [sw36213]
  • manner. Unlike conventional approaches of applying evolution or reinforcement learning over a discrete...
  • Tensorforce

  • Referenced in 4 articles [sw31158]
  • Tensorforce: a TensorFlow library for applied reinforcement learning. Tensorforce is an open-source deep reinforcement...
  • OR-Gym

  • Referenced in 2 articles [sw34774]
  • Operations Research Problem. Reinforcement learning (RL) has been widely applied to game-playing and surpassed ... open-source library for developing reinforcement learning algorithms to address operations ... research problems. In this paper, we apply reinforcement learning to the knapsack, multi-dimensional...
  • Seq2SQL

  • Referenced in 3 articles [sw27204]
  • Structured Queries from Natural Language using Reinforcement Learning. A significant amount of the world ... loop query execution over the database to learn a policy to generate unordered parts ... larger than comparable datasets. By applying policy-based reinforcement learning with a query execution environment...
  • Grad-CAM

  • Referenced in 23 articles [sw35098]
  • tasks with multimodal inputs or reinforcement learning, without any architectural changes or re-training ... high-resolution class-discriminative visualization and apply it to off-the-shelf image classification, captioning...
  • Fullrmc

  • Referenced in 0 articles [sw18974]
  • monte carlo modeling package enabled with machine learning and artificial intelligence. A new Reverse Monte ... contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While ... with no additional programming efforts and to apply smart and more physically meaningful moves...
  • AMC

  • Referenced in 5 articles [sw36241]
  • which leverage reinforcement learning to provide the model compression policy. This learning-based compression policy ... policy for VGG-16 on ImageNet. We applied this automated, push-the-button compression pipeline...
  • ZhuSuan

  • Referenced in 1 article [sw27939]
  • provides deep learning style primitives and algorithms for building probabilistic models and applying Bayesian inference ... advanced gradient estimators (SGVB, REINFORCE, VIMCO, etc.). Importance sampling for learning and evaluating models, with...
  • Meta-AAD

  • Referenced in 2 articles [sw41888]
  • selection. Specifically, Meta-AAD leverages deep reinforcement learning to train the meta-policy to select ... trained meta-policy can be directly applied to any new datasets without further tuning. Extensive...
  • L-VIBRA

  • Referenced in 3 articles [sw02429]
  • Reinforcement Learning approach in the job of learning how to coordinate agent actions ... achieve this goal, a control agent with learning capabilities is introduced in an agent society ... domain on which the system is applied consists of visually guided assembly tasks such...
  • ORL

  • Referenced in 1 article [sw34775]
  • Benchmarks for Online Stochastic Optimization Problems. Reinforcement Learning (RL) has achieved state ... build on this previous work by applying RL algorithms to a selection of canonical online...
  • MazeBase

  • Referenced in 3 articles [sw26504]
  • network, memory network) are deployed via reinforcement learning on these games, with and without ... MazeBase version can be directly applied to StarCraft, where they consistently beat the in-game...
  • Deep4mC

  • Referenced in 1 article [sw40057]
  • found that feature optimization and proper reinforcement learning could improve the performance. We next recollected ... novel deep learning-based 4mC site predictor, namely Deep4mC. Deep4mC applies convolutional neural networks with...
  • DualDICE

  • Referenced in 1 article [sw40535]
  • Distribution Corrections. In many real-world reinforcement learning applications, access to the environment is limited ... present an empirical study of our algorithm applied to off-policy policy evaluation and find...
  • pymgrid

  • Referenced in 1 article [sw36564]
  • Open-Source Python Microgrid Simulator for Applied Artificial Intelligence Research. Microgrids, self contained electrical grids ... pymgrid is built to be a reinforcement learning (RL) platform, and includes the ability...
  • ANSYS

  • Referenced in 713 articles [sw00044]
  • ANSYS offers a comprehensive software suite that spans...
  • Mathematica

  • Referenced in 6445 articles [sw00554]
  • Almost any workflow involves computing results, and that...