Archive
- Using singularity on slurm
- A textured Ouchi Illusion
- Modelling wind ripples
- Implementing a retinotopic transform using `grid_sample` from pyTorch
- Elections présidentielles 2022: estimation du transfert de voix
- COSYNE reviewer feedback
- Dreamachine
- Logistic regression
- Experimenting with transfer learning for visual categorization
- Find a 8 in a forest of 9
- Triangulating stars on the night sky
- Modelling Ocean surface waves
- Density of stars on the surface of the sky
- Time lapsing an orchid's flower
- Kuramoto model
- Generating second-order figures from texture
- Extracting music from the screenshots of a Spotify playlist
- Fitting COVID data
- Benchmarking CNNs
- nesting jupyter runs
- Colors of the sky
- Caustic (optics)
- Creating an hexagonal grid
- Fitting a psychometric curve using pyTorch
- Changing the global phase of a Motion Cloud
- Role of gamma correction in Sparse coding
- Converting a bunch of files in a few lines
- Neurostories: creating videos of the flash-lag effect
- Video abstract for "An Adaptive Homeostatic Algorithm for the Unsupervised Learning of Visual Features"
- Mainen & Sejnowski, 1995
- Generating textures with different complexities
- Origins of the Von Mises distribution
- Sparse coding of large images
- Feature vs global motion
- Embedding a trajectory in noise
- Rainbow effect
- Statistics of the natural input to a ring model
- Extending datasets in pyTorch
- Generating an unique seed for a given filename
- Testing more complex trajectories
- Predictive coding of variable motion
- accessing the data from a pupil recording
- Computing sparseness of natural images with retina-like RFs
- MEUL with a non-parametric homeostasis
- Designing a A0 poster using matplotlib
- Improving calls to the LogGabor library
- The fastest 2D convolution in the world
- Le jeu de l'urne
- testing COMPs-fastPcum_scripted
- testing COMPs-fastPcum
- testing COMPs-Pcum
- A change in the definition of spatial frequency bandwidth?
- Manipulating speed in motion clouds
- Extending Olshausens classical SparseNet
- Reproducing Olshausen's classical SparseNet (part 3)
- Reproducing Olshausens classical SparseNet (part 2)
- Reproducing Olshausen's classical SparseNet (part 1)
- Some basics around probabilities
- Bogacz (2017) A tutorial on free-energy
- Resizing a bunch of files using the command-line interface
- Using generators in Python
- Finding extremal values in a nd-array
- Saving and displaying movies and dynamic figures
- A pi-pie named Monte Carlo
- Une tarte au pi nommée Monte Carlo
- Predictive coding of motion in an aperture
- Static Motion Clouds
- compiling notebooks into a report
- Compiling and using pyNN + NEST + python3
- A bit more fun with gravity waves
- IRM clouds
- Compiling and using pyNN + NEST + python3
- Mirror clouds
- élasticité trames V1
- bootstraping posts for élasticité
- Reproducing Olshausen's classical SparseNet (part 3)
- Reproducing Olshausen's classical SparseNet (part 4)
- élasticité - scénario final montage
- élasticité - scénario onde
- élasticité, geometrie
- élasticité - scénario vague
- élasticité expansion en miroir - dynamique d'un point focal
- élasticité expansion en miroir - exploration paramètres
- élasticité expansion en miroir - principes
- Multiprocessing
- élasticité expansion
- élasticité expansion-réaction diffusion
- élasticité rapsberry pyserial
- élasticité, control scenario
- élasticité, Fresnel
- élasticité, vapory and reflections
- Smooth transition between MCs
- A hitchhiker guide to Matching Pursuit
- A simple pre-processing filter for image processing
- Extending Olshausens classical SparseNet
- Reproducing Olshausens classical SparseNet (part 2)
- Reproducing Olshausen's classical SparseNet (part 1)
- trame-sensorielle
- Moving from Mayavi to VisPy
- MoviePy and python3
- elastic-force
- The Vancouver set
- elastic-grids-of-edges
- Saving files in HoloViews
- An optic flow with Motion Clouds
- Tiling Motion Clouds
- Creating an animation using Gizeh + MoviePy
- Using Tikzmagic
- Rendering 3D scenes in python
- The right imports in a notebook
- Recruiting different population ratios in V1 using orientation components: defining a protocol
- Polar bar plots
- Reading KML My Tracks files in ipython
- Reading KML My Tracks files in ipython
- Reverse-phi and Asymmetry of ON and OFF responses
- Recruiting different population ratios in V1 using orientation components
- Recruiting different population ratios in V1 using orientation components: a biphoton study
- A bit of fun with gravity waves
- Statistics of time-varying images
- Motion Plaids
- Aperture Problem
- Animation in a notebook using holoviews
- Chi distribution
- How can I display an image in the terminal?
- Trying to include javascript in a notebook
- Setting options in holoviews
- Moving from Mayavi to Matplotlib
- transferring (lots of) files to a remote server + saving space
- animation-in-a-notebook
- grille-hexagonale
- [Stage M1] Chloé Pasturel : week 6
- [Stage M1] Chloé Pasturel : week 5
- [Stage M1] Chloé Pasturel : week 4
- [Stage M1] Chloé Pasturel : week 3
- [Stage M1] Chloé Pasturel : week 2
- [Stage M1] Chloé Pasturel : plan du stage
- [Stage M1] Chloé Pasturel : week 1
- Batch removing files on a FTP server
- Converting moinmoin pages to nikola
- Converting MoinMoin pages to Nikola
- Trying out ipython blogging
- 2013-11-12 craac