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zhihanyang2022/README.md

Hi, my name is Zhihan. I work on machine learning research.

Paper implementations:

  • [2024/2] maf-pytorch: Demo PyTorch code for "Masked Autoregressive Flow for Density Estimation" (NIPS 2018)
  • [2024/1] sylvester-flows-pytorch: Demo PyTorch code for "Sylvester Normalizing Flows for Variational Inference" (UAI 2018)
  • [2023/8] normalizing-flows-pytorch: Demo PyTorch code for "Variational Inference with Normalizing Flows" (ICML 2015)
  • [2021/10] off-policy-continuous-control: Official PyTorch code for "Recurrent Off-policy Baselines for Memory-based Continuous Control" (DeepRL Workshop, NeurIPS 2021)

Mini projects:

  • [2023/11] dior: Differentiable reparameterization of matrices with orthogonal columns
  • [2023/9] gradient-gmm: Finite mixture of full-rank Gaussians for density estimation & variational inference
  • [2022/8] aevb-tutorial: Training VAE, conditional VAE, Gaussian Mixture VAE and Variational RNN on MNIST
  • [2022/1] pytorch-ppo: A minimal version of the proximal policy gradient algorithm using the clipped objective
  • [2021/8] alpha-zero: A minimal version of DeepMind's AlphaZero that beats humans on Connect 4

Pinned Loading

  1. off-policy-continuous-control off-policy-continuous-control Public

    Official PyTorch code for "Recurrent Off-policy Baselines for Memory-based Continuous Control" (DeepRL Workshop, NeurIPS 21)

    Python 75 10

  2. gender-audio-classification gender-audio-classification Public

    A speaker gender classifier. MFC feature engineering and a pre-trained ResNet-50. GradCAM interpretation.

    Jupyter Notebook 26 5

  3. alpha-zero alpha-zero Public

    Minimal AlphaZero in PyTorch, trained on Connect4 on a 6x6 board.

    Python 11 2

  4. aevb-tutorial aevb-tutorial Public

    Minimal VAE, Conditional VAE (CVAE), Gaussian Mixture VAE (GMVAE) and Variational RNN (VRNN) in PyTorch, trained on MNIST.

    Jupyter Notebook 9 1

  5. super_mario_as_a_string super_mario_as_a_string Public

    Replication of Super Mario as a String: Platformer Level Generation Via LSTMs. Written in Python using Keras.

    Jupyter Notebook 8 1