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  • Zurich

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Achievement: Pull Shark

Achievements

Achievement: Pull Shark

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AbelHutten/README.md

Highlighted Projects

Deformable Grouped Query Attention

  • Implemented deformable attention with grouped-query support. This is the first known instance of deformable attention enhanced with grouped-query attention, demonstrating a novel architectural combination for improved efficiency.

TEP-Net-V2

  • Experiments on improving TEP-Net, the current SOTA in rail vehicle ego path detection. Added confidence scores, improved out-of-distribution errors when a leading vehicle is close, worked on adding memory to handle otherwise ambiguous cases.
  • Contributed torch.compile integration back to the original TEP-Net, reducing training time by 17.7% on RTX 4090, with potentially greater speedups on datacenter GPUs.

AskePlaat-DRL-Solutions

  • Solutions to most of the questions and many of the practical exersises in the textbook Deep Reinforcent Learning (2022) by Aske Plaat. Made as a reference for people working through these exercises. At the time of writing, the only one on the internet.

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  1. TEP-Net-V2 TEP-Net-V2 Public

    Experiments with TEP-Net (Laurent 2024, arxiv.org/abs/2403.13094), with the goal of improving performance through architectural enhancements.

    Python 2

  2. deformable-grouped-query-attention deformable-grouped-query-attention Public

    Combining Grouped-Query Attention (https://arxiv.org/abs/2305.13245) with Deformable Attention (https://arxiv.org/abs/2201.00520) in PyTorch.

    Python 1

  3. AskePlaat-DRL-Solutions AskePlaat-DRL-Solutions Public

    My solutions to the exercises in "Deep Reinforcement Learning" by Aske Plaat (arxiv.org/abs/2201.02135v5).

  4. cuda_practice cuda_practice Public

    Short programs for practicing CUDA

    Cuda

  5. x86-64-Assembly-Practice x86-64-Assembly-Practice Public

    Some practice x86-64 Linux Assembly programs I wrote while learning x86-64.

    Assembly

  6. pytorch-dqn-replication pytorch-dqn-replication Public

    Replicating the DQN agent from the 2015 Nature paper by Mnih et. al.