Pinned Repositories
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]
Institute for Theoretical Computer Science, TU Graz's Repositories
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/SE-adlif
WIP
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/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/RapidLearningInMemoryComputing
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/TSP
code for Non-synaptic plasticity enables memory-dependent local learning paper