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SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
Steve Brunton
16 พ.ค. 2024
การดู 13,230 ครั้ง
Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering
Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]
Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuition
Why Does Diffusion Work Better than Auto-Regression?
KAN: Kolmogorov–Arnold Networks Paper Explained
Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning
Sparse Identification of Nonlinear Dynamics (SINDy): Sparse Machine Learning Models 5 Years Later!
Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024)
Let's build GPT: from scratch, in code, spelled out.
The Most Important Algorithm in Machine Learning
KAN: Kolmogorov-Arnold Networks | Ziming Liu
What Jumping Spiders Teach Us About Color
แต่ GPT คืออะไร? ภาพแนะนำ Transformers | การเรียนรู้เชิงลึกบทที่ 5
AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]
Understanding the Z-Plane
A Path Towards Autonomous Machine Intelligence with Dr. Yann LeCun
Was "Machine Learning 2.0" All Hype? The Kolmogorov-Arnold Network Explained
Starship Flight 4 Update // Giant Stars Disappearing // Volcanoes on Venus
Reinforcement Learning: Machine Learning Meets Control Theory
Watching Neural Networks Learn