davindicode/UCM-interpret

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davindicode/cosyne-2023-generative-models

Notebooks from the workshop tutorial implementing and discussing a range of generative models commonly used in neuroscience.

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davindicode/davindicode.github.io Fork of barryclark/jekyll-now

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davindicode/nonparametric-nonrenewal-process

We present a flexible modulated point process model for characterising variability in non-stationary neural spike train data.

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davindicode/gpt-engineer Fork of AntonOsika/gpt-engineer

Specify what you want it to build, the AI asks for clarification, and then builds it.

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davindicode/minimal-deep-learning

Minimal implementations and explorations of various deep learning architectures

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davindicode/universal-count-model

We present a probabilistic model for neural spike counts that can capture arbitrary single neuron and joint statistics with their modulation by external covariates.

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davindicode/minGPT Fork of karpathy/minGPT

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

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davindicode/cbl-website Fork of cbl-cambridge/cbl-cambridge.github.io

CBL website

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davindicode/webgl-examples Fork of mdn/webgl-examples

Code examples that accompany the MDN WebGL documentation

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