The Curious Engineer

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Natural Intelligence

greydanus.github.io

A blog by Sam Greydanus

AI / MLMathScience

’16’17’18’19’20’21’22’23’24’25’26
Posts
27 from 5 Aug 2016 to 20 Jul 2026
Posting
now and then (1 in the last year)
Kind
personal blog
Feed
https://greydanus.github.io/feed.xml

2026 1

  1. Pointer Theory

2025 1

  1. The Cursive Transformer

2023 2

  1. Six Experiments in Action Minimization
  2. Finding Paths of Least Action with Gradient Descent

2022 4

  1. Studying Growth with Neural Cellular Automata
  2. A Structural Optimization Tutorial
  3. How Simulating the Universe Could Yield Quantum Mechanics
  4. Dissipative Hamiltonian Neural Networks

2021 1

  1. Piecewise-constant Neural ODEs

2020 7

  1. Scaling down Deep Learning
  2. Optimizing a Wing Inside a Fluid Simulation
  3. The Stepping Stones of Flight
  4. The Story of Flight
  5. Self-classifying MNIST Digits
  6. Lagrangian Neural Networks
  7. The Paths Perspective on Value Learning

2019 2

  1. Neural Reparameterization Improves Structural Optimization
  2. Hamiltonian Neural Networks

2017 5

  1. Visualizing and Understanding Atari Agents
  2. Training Networks in Random Subspaces
  3. Taming Wave Functions with Neural Networks
  4. Differentiable Memory and the Brain
  5. Learning the Enigma with Recurrent Neural Networks

2016 4

  1. A Bird's Eye View of Synthetic Gradients
  2. The Art of Regularization
  3. Scribe: Generating Realistic Handwriting with TensorFlow
  4. Three Perspectives on Deep Learning