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  1. 2017: Change detection: The DivInE-Model
  2. 2017: Computation Spike by Spike
  3. 2017: Contour Integration
  4. 2017: Natural scenes and sparse coding in visual cortex
  5. 2017: Oscillations and information routing: CTC model
  6. 2020: Deep Networks and Tensor Flow
  7. 2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits
  8. 2020: Recurrent networks: Temporal dynamics and synchronization
  9. 2022: Deep Networks and Pytorch
  10. 2022: Divisive inhibition: a dynamical circuit for change detection
  11. 2022: Preparation -- Python class with and without classes
  12. 2022: Synchronization and dynamic oscillations in the visual system
  13. Advanced Indexing
  14. Animation and Slider
  15. Argh: Organize your command line arguments
  16. Assert
  17. Austin: Time and memory profiling
  18. Available dtypes
  19. Basic Commands and Variables
  20. Basic Math Operations
  21. Basic Structure of a Computer
  22. Basics
  23. Basics with Python / Matlab
  24. Beyond normal np.save
  25. Boolean matricies and logic functions
  26. Broadcasting: Automatic adaption of dimensions​
  27. Built-in Functions
  28. Built-in Keywords
  29. Check if the port for torchrun is open via ncat
  30. Class
  31. Collection of distinct hashable objects -- set and frozenset
  32. Computer admin tutorials
  33. Concatenate Matrices and arrays
  34. Config VS Code (Insiders)
  35. Connor Stevens
  36. Constants
  37. Convert other data into numpy arrays e.g. asarray
  38. Converting the original MNIST files into numpy
  39. Creating networks
  40. Creating order via sub-directories: os.makedirs
  41. Data augmentation
  42. Dataclass
  43. Datasets
  44. Dealing with Matlab files
  45. Dealing with the main diagonal / triangles of a matrix
  46. Dict​
  47. Differential Equations
  48. Dimensions and shape
  49. DivInE-model for MT neurons
  50. Dnf and error: rpmdbNextIterator: skipping

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