Institute for Theoretical Computer Science, TU Graz

eligibility_propagation

H-Mem

Code for Limbacher, T. and Legenstein, R. (2020). H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks

L2L

Learning to Learn: Gradient-free Optimization framework

live-plotter

Live plots with matplotlib with a simple interface

LSM

Liquid State Machines in Python and NEST

LSNN-official

Long short-term memory Spiking Neural Networks

SimManager

The Simulation Manager is a library for enabling reproducible scientific simulations.

SimRecorder

An high-performance library for recording and storing simulation data

spore-nest-module

Synaptic Plasticity with Online Reinforcement learning

WeatherDiffusion

Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]

IGITUGraz/WeatherDiffusion

Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]

IGITUGraz/LSNN-official

Long short-term memory Spiking Neural Networks

IGITUGraz/eligibility_propagation

IGITUGraz/LSM

Liquid State Machines in Python and NEST

IGITUGraz/L2L

Learning to Learn: Gradient-free Optimization framework

IGITUGraz/H-Mem

Code for Limbacher, T. and Legenstein, R. (2020). H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks

IGITUGraz/Cognitive-Map-Learner

This repo contains an example jupyter-notebook for the CML algorithm on all different kinds of the abstract random graph tasks.

IGITUGraz/SimManager

The Simulation Manager is a library for enabling reproducible scientific simulations.

IGITUGraz/SparseAdversarialTraining

Code for "Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling" [ICML 2021]

IGITUGraz/MemoryDependentComputation

Code for Limbacher, T., Özdenizci, O., & Legenstein, R. (2022). Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. arXiv preprint arXiv:2205.11276.

IGITUGraz/structured_information_representation

Simulation code für Müller et al., A model for structured information representation in neural networks of the brain

IGITUGraz/IGI-Reading-Group

IGI Reading Group

IGITUGraz/OutputCodeMatching

Code for "Improving Robustness Against Stealthy Weight Bit-Flip Attacks by Output Code Matching" [CVPR 2022]

IGITUGraz/Spike-Frequency-Adaptation-Supports-Network-Computations

Code for: Spike Frequency Adaptation Supports Network Computations on Temporally Dispersed Information

IGITUGraz/CSNN

IGITUGraz/dendritic_rewiring

Simulation code for Limbacher, T. and Legenstein, R. (2020). Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring

IGITUGraz/scoop

SCOOP (Scalable COncurrent Operations in Python)

IGITUGraz/SimRecorder

An high-performance library for recording and storing simulation data

IGITUGraz/SE-adlif

WIP

IGITUGraz/RobustSNNConversion

Code for "Adversarially Robust Spiking Neural Networks Through Conversion" [TMLR 2024]

IGITUGraz/StraightSkel

StraightSkel is an implementation of the Straight Skeleton in 2- and 3-dimensional space. It is used to animate the computation of offsets of polygons and polyhedrons. StraightSkel was written by Gernot Walzl in the years 2011, 2012, 2013, 2016

IGITUGraz/adaptation_working_memory

Spike frequency adaptation supports network computations on temporally dispersed information

IGITUGraz/dynamic_rnn_with_gradients

IGITUGraz/Fault-Pruning

Code for: Kraišniković, C., Stathopoulos, S., Prodromakis, T., & Legenstein, R. (2023, March). Fault pruning: Robust training of neural networks with memristive weights. In International Conference on Unconventional Computation and Natural Computation (pp. 124-139). Cham: Springer Nature Switzerland.

IGITUGraz/QuantizedRewiring

IGITUGraz/RobustModelCompression

Code for "Preserving Real-World Robustness of Neural Networks Under Sparsity Constraints" [ECML-PKDD 2024]

IGITUGraz/loggingext

Short for Logging Extensions, contains helper functions for python logging

IGITUGraz/LookbackNeuron

NEST related header and source files containing the relevant code to implement the feature of looking back into incoming synapses.

IGITUGraz/RapidLearningInMemoryComputing

IGITUGraz/TSP

code for Non-synaptic plasticity enables memory-dependent local learning paper