Multivariate Probabilistic Time Series Forecasting with Informer
Efficient transformer-based model for LSTF.
Method introduces a Probabilistic Attention mechanism to select the “active” queries rather than the “lazy” queries and provides a sparse Transformer thus mitigating the quadratic compute and memory requirements of vanilla attention.
🤗Hugging face:
https://huggingface.co/blog/informer
⏩ Paper:
https://huggingface.co/docs/transformers/main/en/model_doc/informer
⭐️ Colab:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multivariate_informer.ipynb
💨 Dataset:
https://huggingface.co/docs/datasets/v2.7.0/en/package_reference/main_classes#datasets.Dataset.set_transform
https://t.iss.one/DataScienceT
Efficient transformer-based model for LSTF.
Method introduces a Probabilistic Attention mechanism to select the “active” queries rather than the “lazy” queries and provides a sparse Transformer thus mitigating the quadratic compute and memory requirements of vanilla attention.
🤗Hugging face:
https://huggingface.co/blog/informer
⏩ Paper:
https://huggingface.co/docs/transformers/main/en/model_doc/informer
⭐️ Colab:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multivariate_informer.ipynb
💨 Dataset:
https://huggingface.co/docs/datasets/v2.7.0/en/package_reference/main_classes#datasets.Dataset.set_transform
https://t.iss.one/DataScienceT
❤🔥2👍1
✨DigiData: Training and Evaluating General-Purpose Mobile Control Agents
📝 Summary:
DigiData provides a diverse, high-quality dataset for training mobile control agents with complex goals from app feature exploration. DigiData-Bench offers dynamic AI-powered evaluation protocols, improving agent assessment beyond common metrics.
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07413
• PDF: https://arxiv.org/pdf/2511.07413
• Github: https://facebookresearch.github.io/DigiData
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MobileAgents #ArtificialIntelligence #MachineLearning #Datasets #AgentTraining
📝 Summary:
DigiData provides a diverse, high-quality dataset for training mobile control agents with complex goals from app feature exploration. DigiData-Bench offers dynamic AI-powered evaluation protocols, improving agent assessment beyond common metrics.
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07413
• PDF: https://arxiv.org/pdf/2511.07413
• Github: https://facebookresearch.github.io/DigiData
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MobileAgents #ArtificialIntelligence #MachineLearning #Datasets #AgentTraining
❤1
✨Grounding Computer Use Agents on Human Demonstrations
📝 Summary:
GroundCUA is a large desktop grounding dataset built from expert human demonstrations. It enables GroundNext models to achieve state-of-the-art performance in mapping instructions to UI elements with less training data and strong agentic capabilities.
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07332
• PDF: https://arxiv.org/pdf/2511.07332
• Project Page: https://groundcua.github.io/
• Github: https://groundcua.github.io/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #Agents #HCI #Datasets #HumanDemonstrations
📝 Summary:
GroundCUA is a large desktop grounding dataset built from expert human demonstrations. It enables GroundNext models to achieve state-of-the-art performance in mapping instructions to UI elements with less training data and strong agentic capabilities.
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07332
• PDF: https://arxiv.org/pdf/2511.07332
• Project Page: https://groundcua.github.io/
• Github: https://groundcua.github.io/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #Agents #HCI #Datasets #HumanDemonstrations