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Graphium-专注于图表示学习的深度学习库

Graphium是一个专注于图表示学习的深度学习库,特别用于处理现实世界中的化学任务。它具备最先进的图神经网络架构,提供可扩展的API,并支持丰富的分子特征化功能,能够有效应对复...

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Graphium是一个专注于图表示学习的深度学习库,特别用于处理现实世界中的化学任务。它具备最先进的图神经网络架构,提供可扩展的API,并支持丰富的分子特征化功能,能够有效应对复杂的化学问题。
Graphium的特点:
1. 最先进的图神经网络架构
2. 可扩展的API
3. 丰富的分子特征化
4. 支持处理复杂的化学任务

Graphium的功能:
1. 用于分子结构的图表示学习
2. 实现化学任务的深度学习模型
3. 进行分子特征提取和分析
4. 扩展和自定义图神经网络架构

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name: “Sapiens: Foundation for Human Vision Models” description: “A foundation for human vision models.” url: “github.com/facebookresearch/sapiens” features:   – “Focuses on human vision modeling.”   – “Supports various vision tasks.” usage:   – “Used for training vision models.”   – “Applicable in research related to human vision.”  name: “E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS” description: “A text-to-speech model that is fully non-autoregressive and zero-shot.” url: “github.com/bfs18/e2_tts” features:   – “Non-autoregressive architecture.”   – “Zero-shot capabilities.” usage:   – “Used for text-to-speech applications.”   – “Can be applied in voice synthesis tasks.”  name: “Scalable Autoregressive Image Generation with Mamba” description: “An autoregressive model for scalable image generation.” url: “github.com/hp-l33/AiM” features:   – “Scalable image generation.”   – “Autoregressive model design.” usage:   – “Used for generating high-quality images.”   – “Applicable in creative design and art generation.”  name: “TraDiffusion: Trajectory-Based Training-Free Image Generation” description: “A framework for training-free image generation based on trajectories.” url: “github.com/och-mac/TraDiffusion” features:   – “Training-free approach.”   – “Utilizes trajectory-based generation.” usage:   – “Can be used in generative model research.”   – “Applicable for creating images without extensive training.”  name: “Training-free Graph Neural Networks and the Power of Labels as Features” description: “A framework for training-free graph neural networks leveraging labels.” url: “github.com/joisino/laf” features:   – “Training-free method.”   – “Incorporates labels as features.” usage:   – “Used in graph-based learning tasks.”   – “Applicable in scenarios where labeled data is available.”  name: “TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models” description: “A framework for evaluating video foundation models.” url: “github.com/twelvelabs-io/video-embeddings-evaluation-framework” features:   – “Holistic evaluation of video models.”   – “Provides insights into model performance.” usage:   – “Used for assessing video model quality.”   – “Applicable for research in video analytics.”  name: “STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics” description: “A dataset for studying histopathology images and gene expressions.” url: “github.com/JiawenChenn/STimage-1K4M” features:   – “Focus on histopathology and gene expression.”   – “Large dataset for spatial transcriptomics.” usage:   – “Used in biomedical research.”   – “Applicable for training models in histopathology analysis.”-组织病理图像数据集
name: “Sapiens: Foundation for Human Vision Models” description: “A foundation for human vision models.” url: “github.com/facebookresearch/sapiens” features:   – “Focuses on human vision modeling.”   – “Supports various vision tasks.” usage:   – “Used for training vision models.”   – “Applicable in research related to human vision.”  name: “E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS” description: “A text-to-speech model that is fully non-autoregressive and zero-shot.” url: “github.com/bfs18/e2_tts” features:   – “Non-autoregressive architecture.”   – “Zero-shot capabilities.” usage:   – “Used for text-to-speech applications.”   – “Can be applied in voice synthesis tasks.”  name: “Scalable Autoregressive Image Generation with Mamba” description: “An autoregressive model for scalable image generation.” url: “github.com/hp-l33/AiM” features:   – “Scalable image generation.”   – “Autoregressive model design.” usage:   – “Used for generating high-quality images.”   – “Applicable in creative design and art generation.”  name: “TraDiffusion: Trajectory-Based Training-Free Image Generation” description: “A framework for training-free image generation based on trajectories.” url: “github.com/och-mac/TraDiffusion” features:   – “Training-free approach.”   – “Utilizes trajectory-based generation.” usage:   – “Can be used in generative model research.”   – “Applicable for creating images without extensive training.”  name: “Training-free Graph Neural Networks and the Power of Labels as Features” description: “A framework for training-free graph neural networks leveraging labels.” url: “github.com/joisino/laf” features:   – “Training-free method.”   – “Incorporates labels as features.” usage:   – “Used in graph-based learning tasks.”   – “Applicable in scenarios where labeled data is available.”  name: “TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models” description: “A framework for evaluating video foundation models.” url: “github.com/twelvelabs-io/video-embeddings-evaluation-framework” features:   – “Holistic evaluation of video models.”   – “Provides insights into model performance.” usage:   – “Used for assessing video model quality.”   – “Applicable for research in video analytics.”  name: “STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics” description: “A dataset for studying histopathology images and gene expressions.” url: “github.com/JiawenChenn/STimage-1K4M” features:   – “Focus on histopathology and gene expression.”   – “Large dataset for spatial transcriptomics.” usage:   – “Used in biomedical research.”   – “Applicable for training models in histopathology analysis.”-组织病理图像数据集
Nname: “Sapiens: Foundation for Human Vision Models” description: “A foundation for human vision models.” url: “github.com/facebookresearch/sapiens” features: – “Focuses on human vision modeling.” – “Supports various vision tasks.” usage: – “Used for training vision models.” – “Applicable in research related to human vision.” name: “E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS” description: “A text-to-speech model that is fully non-autoregressive and zero-shot.” url: “github.com/bfs18/e2_tts” features: – “Non-autoregressive architecture.” – “Zero-shot capabilities.” usage: – “Used for text-to-speech applications.” – “Can be applied in voice synthesis tasks.” name: “Scalable Autoregressive Image Generation with Mamba” description: “An autoregressive model for scalable image generation.” url: “github.com/hp-l33/AiM” features: – “Scalable image generation.” – “Autoregressive model design.” usage: – “Used for generating high-quality images.” – “Applicable in creative design and art generation.” name: “TraDiffusion: Trajectory-Based Training-Free Image Generation” description: “A framework for training-free image generation based on trajectories.” url: “github.com/och-mac/TraDiffusion” features: – “Training-free approach.” – “Utilizes trajectory-based generation.” usage: – “Can be used in generative model research.” – “Applicable for creating images without extensive training.” name: “Training-free Graph Neural Networks and the Power of Labels as Features” description: “A framework for training-free graph neural networks leveraging labels.” url: “github.com/joisino/laf” features: – “Training-free method.” – “Incorporates labels as features.” usage: – “Used in graph-based learning tasks.” – “Applicable in scenarios where labeled data is available.” name: “TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models” description: “A framework for evaluating video foundation models.” url: “github.com/twelvelabs-io/video-embeddings-evaluation-framework” features: – “Holistic evaluation of video models.” – “Provides insights into model performance.” usage: – “Used for assessing video model quality.” – “Applicable for research in video analytics.” name: “STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics” description: “A dataset for studying histopathology images and gene expressions.” url: “github.com/JiawenChenn/STimage-1K4M” features: – “Focus on histopathology and gene expression.” – “Large dataset for spatial transcriptomics.” usage: – “Used in biomedical research.” – “Applicable for training models in histopathology analysis.”-组织病理图像数据集

一个用于研究组织病理图像和基因表达的数据库,支持空间转录组学研究。

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