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chapter 2 of IOT A hands on Approach
Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs
In this presentation, I provided a comprehensive introduction to the information retrieval and large...
all main point
OTBI slides from Open World 2013
Graph Representation Learning Meets Computer Vision: A Survey
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships
General presentation about the word2vec model, including some explanations for training and referen...
Barthes’ five narrative codes Textual analysis and represntation
PoolParty is a world-leading semantic technology platform focusing on standards-based management of ...
Creating datasets with dbt is faster and more scalable than using drag-and-drop tools, stored proced...
In this engaging 20-minute talk, we'll explore how modern cloud architectures and advanced data ...
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction
Slideshow with information on macro features and the main types of macro features which are analysed...
It is an ICT tool for screening student with specific learning disabilities
GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks
U-Net
🎓 1회차: 데이터 저장소 계층 – RAG의 기억 구조
Query Processing : Query Processing Problem, Layers of Query Processing Query Processing in Centrali...
Mask R-CNN present a conceptually simple, flexible, and general framework for object instance segmen...
Distributed Database Systems
Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion
AUTOENCODER AND ITS TYPES , HOW ITS USED, APPLICATIONS , ADVANTAGES AND DISADVANTAGES OF AUTOENCODER
This is a test document that is used to satisfy the requirement to upload two documents.
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![[NS][Lab_Seminar_240610]Graph Representation Learning Meets Computer Vision: A Survey.pptx](https://slidepub.com/thumb/9561/269849561.jpg)
![240527_Thanh_LabSeminar[Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships].pptx](https://slidepub.com/thumb/1656/269481656.jpg)
![[DSC DACH 24] Ship data faster with dbt - Sean McIntyre](https://slidepub.com/thumb/6851/271936851.jpg)
![[DSC DACH 24] Bridging the Technical-Business Divide with Modern Cloud Architectures and Data Catalogs - Boris Perkovic](https://slidepub.com/thumb/6922/271936922.jpg)
![[20240710_LabSeminar_Huy]PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction.pptx](https://slidepub.com/thumb/3004/270433004.jpg)
![[20240805_LabSeminar_Huy]GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks.pptx](https://slidepub.com/thumb/4481/270804481.jpg)
![240603_Thanh_LabSeminar[Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion].pptx](https://slidepub.com/thumb/1603/269481603.jpg)
