Showing 6 open source projects for "spectra deep learning"

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  • 1
    AirSim

    AirSim

    A simulator for drones, cars and more, built on Unreal Engine

    ... a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. AirSim is fully enabled for multiple vehicles. This capability allows you to create multiple vehicles easily and use APIs to control them.
    Downloads: 73 This Week
    Last Update:
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  • 2
    Bullet Physics SDK

    Bullet Physics SDK

    Real-time collision detection and multi-physics simulation for VR

    ... using Deep Reinforcement Learning, or using Gradient based optimization (for example LFBGS). In addition, the simulator can be entirely run on CUDA for fast rollouts, in combination with Augmented Random Search. This allows for 1 million simulation steps per second. It is highly recommended to use PyBullet Python bindings for improved support for robotics, reinforcement learning and VR. Use pip install pybullet and checkout the PyBullet Quickstart Guide.
    Downloads: 10 This Week
    Last Update:
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  • 3
    ViZDoom

    ViZDoom

    Doom-based AI research platform for reinforcement learning

    ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. ViZDoom is based on ZDOOM, the most popular modern source-port of DOOM. This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community...
    Downloads: 1 This Week
    Last Update:
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  • 4
    Euler

    Euler

    A distributed graph deep learning framework.

    ... for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle.
    Downloads: 5 This Week
    Last Update:
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  • 5
    TorchCraft

    TorchCraft

    Connecting Torch to StarCraft

    We present TorchCraft, a library that enables deep learning research on Real-Time Strategy (RTS) games such as StarCraft: Brood War, by making it easier to control these games from a machine learning framework, here Torch. This white paper argues for using RTS games as a benchmark for AI research, and describes the design and components of TorchCraft. TorchCraft is a BWAPI module that sends StarCraft data out over a ZMQ connection. This lets you parse StarCraft data and interact with BWAPI from...
    Downloads: 0 This Week
    Last Update:
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  • 6
    Deep Space Pirates
    A space combat simulator game/learning project. All the info in our wiki: https://sourceforge.net/apps/mediawiki/dspirates/index.php?title=Main_Page Our code at: https://deepspacepirates.codeplex.com/SourceControl/latest
    Downloads: 3 This Week
    Last Update:
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