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Spiking Neural Network (SNN) — Neuromorphic Computing
Predictive Coding
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Hopfield Networks
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Reinforcement Learning in the Brain
Free Energy Principle
Attractor Networks
Neural Population Dynamics
Drift-Diffusion Model
Efficient Coding Hypothesis
Divisive Normalization
Synaptic Plasticity Models
Deep Learning vs Brain
Reservoir Computing
Compartmental Models
Whole-Brain Modeling
Information Theory in Neuroscience
Neural ODEs & Continuous-Time Models
Energy-Based Models & the Brain
Table of Contents
1. Basics
2. Hebbian Storage
3. Recall Process
4. PyTorch — Hopfield
5. Neuroscience Mapping
6. Modern Hopfield Network (Ramsauer 2020)
7. Hopfield ↔ Boltzmann Machine
8. Spin Glass Analogy
9. Limitations
10. Common Pitfalls
10.1 Storing > 0.138N
10.2 W Not Symmetric
10.3 Energy Monotone Decrease
10.4 Hopfield = LSTM Error
10.5 Modern Hopfield ≠ Classical
11. Related Concepts
References