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Panda, a model trained on synthetic chaotic systems, achieves zero-shot forecasting and nonlinear resonance patterns, demonstrating potential for predicting real-world dynamics without retraining on diverse datasets.
https://arxiv.org/abs//2505.13755
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
5
33 ratings
Panda, a model trained on synthetic chaotic systems, achieves zero-shot forecasting and nonlinear resonance patterns, demonstrating potential for predicting real-world dynamics without retraining on diverse datasets.
https://arxiv.org/abs//2505.13755
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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