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

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。

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.”的特点:

• 1. 专注于组织病理学和基因表达。
• 2. 大型空间转录组学数据集。

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.”的功能:

• 1. 用于生物医学研究。
• 2. 适用于组织病理分析模型的训练。