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Learning to learn: An Introduction to Meta Learning

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Transformer

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iMAML: Meta-Learning with Implicit Gradients (Paper Explained)

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Supervised Contrastive Learning

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DRL Lecture 2: Proximal Policy Optimization (PPO)

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Deep Learning 59: Fundamentals of Graph Neural Network

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【機器學習 2022】各式各樣神奇的自注意力機制 (Self-attention) 變型

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[TA 補充課] SAGAN, BigGAN, SinGAN, GauGAN, GANILLA, NICE-GAN (由助教吳宗翰同學講授)

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[TA 補充課] Optimization for Deep Learning (1/2) (由助教簡仲明同學講授)

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[TA 補充課] More about Adversarial Attack (2/2) (由助教黃冠博同學講授)

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[TA 補充課] Network Compression (2/2): Network Pruning (由助教劉俊緯同學講授)

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[TA 補充課] Optimization for Deep Learning (2/2) (由助教簡仲明同學講授)

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[TA 補充課] Network Compression (1/2): Knowledge Distillation (由助教劉俊緯同學講授)

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[TA 補充課] RL - Model-based, Large-scale, Meta, Multi-agent, Hide-and-seek, Alpha Star (由助教林義聖同學講授)

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