A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...

Actively developed Hierarchical Temporal Memory (HTM) community fork (continuation) of NuPIC. Implementation for C++ and Python

Code behind the work "Single Cortical Neurons as Deep Artificial Neural Networks", published in Neuron 2021

ConvRNN Model Zoo: ImageNet pre-trained convolutional recurrent neural networks

Code for our AAMAS 2020 paper: "A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry".

Axon is a spiking, biologically-based neural model driven by predictive error-driven learning, for systems-level models of the brain

"The Unreasonable Effectiveness of Sparse Dynamic Synapses for Continual Learning" paper project.

Implementation of BIMRL: Brain Inspired Meta Reinforcement Learning - Roozbeh Razavi et al. (IROS 2022)

Code behind the work "Multiple Synaptic Contacts Combined with Dendritic Filtering Enhance Spatio-Temporal Pattern Recognition of Single Neurons", bioRxiv 2022

Models of Mouse Vision: Self-supervised pre-trained networks and training code (PyTorch)

Official Repository of the "How to Learn and Represent Abstractions: An Investigation using Symbolic Alchemy" Paper

Artificial Biological Intelligence

Quantum neural network research implementing multi-dimensional neuron representations. Explores theoretical integration of quantum computing principles into neural systems to investigate emergent cognition and consciousness.

Multi Task Neural Network for Grasping and Classification

Polished code for "Can a single neuron solve MNIST? The computational power of biological dendritic trees”

The Inattentive Interview

Computational Neuroscience models