Foundations for advanced learners
588 resources · page 19 of 19
Switch Transformers
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arXiv paper (2021) introducing Switch Transformers, sparse mixture-of-experts models scaled to a trillion parameters.
A decoder-only foundation model for time-series forecasting (TimesFM)
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arXiv paper (2023) introducing TimesFM, a decoder-only foundation model for time-series forecasting.
tslearn
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tslearn documentation: Python machine learning tools for time-series analysis.
U-Net
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arXiv paper (2015) "U-Net: Convolutional Networks for Biomedical Image Segmentation", introducing the encoder-decoder architecture with skip connections.
Umar Jamil (YouTube)
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Umar Jamil's YouTube channel: line-by-line implementations of Transformer, LLaMA and diffusion models.
verifiers v1
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Prime Intellect post on verifiers v1, splitting environments into tasksets, harnesses and runtimes for agentic RL and evals.
VGG
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arXiv PDF of the VGG paper (2014) on very deep convolutional networks for large-scale image recognition.
ViT
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arXiv paper (2020) introducing the Vision Transformer (ViT) for image recognition.
WaveNet
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arXiv paper (2016) "WaveNet: A Generative Model for Raw Audio", introducing WaveNet, an autoregressive generative model of raw audio.
Wide & Deep
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arXiv paper (2016) "Wide & Deep Learning for Recommender Systems", introducing Google's Wide & Deep recommender model.
xLSTM (NXAI, Linz)
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arXiv paper (2024) introducing xLSTM, extended long short-term memory with exponential gating and matrix memory.
YOLO
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arXiv paper (2015) "You Only Look Once: Unified, Real-Time Object Detection", introducing YOLO, a single-stage real-time object detector.