محمد گنج تابش

2. Meta-learning in spiking neural networks with reward-modulated STDP

Gholamzadeh Khoee Arsham، Javaheri Alireza، Kheradpisheh Saeed Reza، Ganjtabesh Mohammad (2024)., NEUROCOMPUTING, 600(1), 128173.

3. Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks

Nadafian Neghabi Alireza، Ganjtabesh Mohammad (2024)., NEURAL COMPUTATION, 36(7), 1-21.

1. Accelerating spiking neural network simulations with PymoNNto and PymoNNtorch

Vieth Marius، Rahimi Ali، Gorgan Mohammadi Ashena، Triesch Jochen، Ganjtabesh Mohammad (2024)., Frontiers in Neuroinformatics, 18(1331220).

2. On computational models of theory of mind and the imitative reinforcement learning in spiking neural networks

Gorgan Mohammadi Ashena، Ganjtabesh Mohammad (2024)., Scientific Reports, 14(1).

2. Avid: A Variational Inference Deliberation For Meta-Learning

Javaheri Alireza، Kheradpisheh Saeed Reza، Farahani Hadi، Gholamzadeh Khoee Arsham، Ganjtabesh Mohammad (2022)., 2022 12th International Conference on Computer and Knowledge Engineering (ICCKE), 17-18 November, Iran.

1. Top-Down modulated model for object recognition in different categorization levels

Sharifizadeh Fatemeh، Ganjtabesh Mohammad، Nouzari Dalini Abbas (2021)., International Journal of Bio-Inspired Computation, 18(1).

1. Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks

Mozafari Milad، Ganjtabesh Mohammad، Nouzari Dalini Abbas، Thorpe Simon، Masquelier Timothee (2019)., PATTERN RECOGNITION, 94(1), 87-95.

2. SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron

Mozafari Milad، Ganjtabesh Mohammad، Nouzari Dalini Abbas، Masquelier Timothee (2019)., Frontiers in Neuroscience, 13(1).

1. First-Spike-Based Visual Categorization Using Reward-Modulated STDP

Mozafari Milad، Kheradpisheh Saeed Reza، Masquelier Timothee، Nouzari Dalini Abbas، Ganjtabesh Mohammad (2018)., IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 29(12), 6178-6190.

3. Top-Down Modulated Model for Object Recognition in Different Categorization Levels

Sharifizadeh Fatemeh، Ganjtabesh Mohammad، Nouzari Dalini Abbas (2018)., Two-Day Symposium on Theoretical and Computational Neuroscience, 16-17 April, Tehran, Iran.

1. STDP-based spiking deep convolutional neural networks for object recognition

Kheradpisheh Saeed Reza، Ganjtabesh Mohammad، Masquelier Timothee، Thorpe Simon (2018)., NEURAL NETWORKS, 99(1), 56-67.

2. RNA Secondary Structure: the inverse folding problem

Ganjtabesh Mohammad (2018)., The 7th Bioinformatics Conference of Iran, 3-5 January, Tehran, Iran.

4. Evaluating the quality of SHAPE data simulated by k-mers for RNA structure prediction

Montaseri Soheila، فاطمه زارع میرک اباد، Ganjtabesh Mohammad (2017)., Journal of Bioinformatics and Computational Biology, 15(06), 1750023.

5. RNA Secondary Structure Prediction Using Genetic Algorithm

Ganjtabesh Mohammad، Chenaghloo Milad، Nouzari Dalini Abbas (2017)., Bioinformatics and Biocomputational Research, 1(2), 59-62.

6. Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

Najar Ashtiani Matin، Kheradpisheh Saeed Reza، Masquelier Timothee، Ganjtabesh Mohammad (2017)., Frontiers in Psychology, 8(1), 1261.

2. Improving protein complex prediction by reconstructing a high-confidence protein-protein interaction network of Escherichia coli from different physical interaction data sources

Taghipour Shirin، Zarrineh Peyman، Ganjtabesh Mohammad، Nouzari Dalini Abbas (2017)., BMC BIOINFORMATICS, 18(1), 1.

3. Evolutionary Algorithm for RNA Secondary Structure Prediction Based on Simulated SHAPE Data

Montaseri Soheila، Ganjtabesh Mohammad، فاطمه زارع میرک اباد (2016)., PLoS One, 11(11), e0166965.