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Measuring the ripeness of fruit with Hyperspectral Imaging and Deep Learning
MMGX: Multiple Molecular Graph eXplainable Discovery
[WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.
[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记
Text Diffusion Model with Encoder-Decoder Transformers for Sequence-to-Sequence Generation [NAACL 2024]
DiffusionFastForward: a free course and experimental framework for diffusion-based generative models
This is for an assignment for my Deep Learning class. What I did is doing latent diffusion from scratch. smallNORB Dataset is used to train the neural networks.
Implementation of a Latent Diffusion
Latent Diffusion Model for DNA Sequence Generation
Conditional denoising diffusion probabilistic model trained in latent space.
[NeurIPS 2023] Official implementation of "PreDiff: Precipitation Nowcasting with Latent Diffusion Models"
[ICML 2022] Latent Diffusion Energy-Based Model for Interpretable Text Modeling
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
A practice example of latent diffusion
[CVPR 2023] Executing your Commands via Motion Diffusion in Latent Space, a fast and high-quality motion diffusion model
Takagi and Nishimoto, CVPR 2023
Official implementation for Learning Invariant Molecular Representation in Latent Discrete Space (NeurIPS 2023)
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
Code for UniS-MMC: Multimodal Classification via Unimodality-supervised Multimodal Contrastive Learning (ACL 2023)
The official codes and implementations of HimGNN model in paper:"HimGNN:a novel hierarchical molecular representations learning framework for property prediction"
CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)