Showing 6 open source projects for "search engine optimization"

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    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization

    Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms.
    Downloads: 0 This Week
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  • 2
    EvoTorch

    EvoTorch

    Advanced evolutionary computation library built on top of PyTorch

    EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods.
    Downloads: 0 This Week
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  • 3
    Brax

    Brax

    Massively parallel rigidbody physics simulation

    Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization.
    Downloads: 0 This Week
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  • 4
    Ray

    Ray

    A unified framework for scalable computing

    ...Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. ...
    Downloads: 0 This Week
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    Bullet Physics SDK

    Bullet Physics SDK

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

    ...It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained 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: 6 This Week
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  • 6
    CCZero (中国象棋Zero)

    CCZero (中国象棋Zero)

    Implement AlphaZero/AlphaGo Zero methods on Chinese chess

    ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics.
    Downloads: 0 This Week
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