#time-series
3 posts · all tags
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· Diffusion models for time series
On this post I will explore the main findings from the paper UTSD: Unified Time Series Diffusion Model and an explanation of the content. For more details here is the link to the paper Link to paper
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· Temporal Graph Networks: A Deep Dive into Dynamic Graph Learning
Real-world networks are rarely static. Social networks evolve as users form new connections, financial networks change with each transaction, and biological networks transform as proteins interact. Traditional Graph Neural Networks (GNNs) weren't designed for this dynamism. Enter Temporal Graph Networks (TGNs), a powerful framework for learning on dynamic graphs.
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· Implementing the Kalman Filter in Python
Hello. I'm trying to experiment with some recent articles that tries to connect transformers and kalman filter. I remember that I saw in my undergrad this concept on the control lecture but to be honest I didn't quite understand the concept at the time. To help my understanding i tried to implement using only some basic python libraries the Kalman Filter in python.