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BeiJing

Tao Yang

Advanced
@ThomasMrY

Countably infinite

DisDiff. [NeurIPS 2023] code for "DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

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VCT. [NeurIPS 2022] code for "Visual Concepts Tokenization"

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EncDiff. [NeurIPS 2024 Spotlight] code for "Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement"

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ActivationFunctionDemo. [TCAD 2018] Code for “Design Space Exploration of Neural Network Activation Function Circuits”

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Groupified-VAE. [ICLR 2022] code for "Towards building a group-based unsupervised representation disentanglement framework"

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ASE-Pair-Programing-Project. How is the 26-letter frequency of English distributed in a novel? What are the words that often appear in a type of article? What is the most commonly used term for a writer? What is the most commonly used phrase in Harry Potter, and so on. We will write some procedures to solve this problem and satisfy our curiosity.

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RF-VAE. Pytorch implementation of RF_VAE proposed in Relevance Factor VAE: Learning and Identifying Disentangled Factors, Kim et al.

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ThomasNotes. This is a repository of my own learning notes, also could be a tutorial. I will I will continue to update this new repository, which may include machine learning, deep learning, probability theory, information theory, pytorch, tensorflow, and some learning materials from numpy, which may be partially non-original but could be useful.

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DisCo. [ICLR2022] Code for "Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View"

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origin. This code is for generating the parameters before multi-value operation.

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Poetic-Image. software engineering team project

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CS-DisMo. Code for paper "Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement"

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ternary-cnn. This code ternary the output of the neural networks.

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DockerFile. The DockerFile of OpenPAI

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binary-cov. This code binary the output of the convolution layer of CNN and train and prune the parameters.

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Anotool. The "Anotool" is a demo for labeling multi-attribute object labels for images, with hierarchical attributes and objects, which is the anotation tool of the dataset and the paper:

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