This repository is an archive of work done in exploring recurrent temporal neural networks (rTNNs) in 18847-Neuromorphic Computing Architecture.
The top-level directories are:
- SpykeTorch - scripts used for Lab1 in TNN column implementation
- bindsnet_reference - contains slightly modified reservoir reference template from BindsNET
- recurrent_only_scripts - contains variants of recurrent-only architecture
Additional top level files are:
- seq_mnist_pix.py - pixel by pixel sequential MNIST template using reservoirs
- seq_mnist_row.py - row by row sequential MNIST template using reservoirs
- TNN.py - implementations of our extensions to BindsNET for TNN simulation
- TNN_utils.py - utilities used in implementations of recurrent-only rTNN architecture
- rc_template-seq.py - reservoir computing template on sequential mnist
- rc_template.py - general reservoir computing template
- rc_template_buff_seq.py - reservoir computing template using TNN neurons and buffer nodes
- stateful_tnn.py - implementation of stateful rTNN architecture
- test_TNN.py
- test_TNN_2layer.py - implementation of 2-layer rTNN architecture
- test_TNN_lr_readout.py - implementation of TNN column with logistic regression readout
- test_TNN_w_on_off.py
- test_buffer_nodes.py
- tnn_inhibt_recur_TNN.py
Running these codes requires an installation of BindsNET. More details on that can be found here: https://github.com/BindsNET/bindsnet.