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Dan Saunders
Dan Saunders
Unknown affiliation
Verified email at cs.umass.edu - Homepage
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Bindsnet: A machine learning-oriented spiking neural networks library in python
H Hazan, DJ Saunders, H Khan, D Patel, DT Sanghavi, HT Siegelmann, ...
Frontiers in neuroinformatics 12, 89, 2018
2972018
Unsupervised learning with self-organizing spiking neural networks
H Hazan, D Saunders, DT Sanghavi, H Siegelmann, R Kozma
2018 International Joint Conference on Neural Networks (IJCNN), 1-6, 2018
862018
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game
D Patel, H Hazan, DJ Saunders, HT Siegelmann, R Kozma
Neural Networks 120, 108-115, 2019
772019
Locally connected spiking neural networks for unsupervised feature learning
DJ Saunders, D Patel, H Hazan, HT Siegelmann, R Kozma
Neural Networks 119, 332-340, 2019
602019
STDP learning of image patches with convolutional spiking neural networks
DJ Saunders, HT Siegelmann, R Kozma
2018 international joint conference on neural networks (IJCNN), 1-7, 2018
472018
Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data
H Hazan, DJ Saunders, DT Sanghavi, H Siegelmann, R Kozma
Annals of Mathematics and Artificial Intelligence 88, 1237-1260, 2020
212020
Reasoning and generalization in rl: A tool use perspective
S Wenke, D Saunders, M Qiu, J Fleming
arXiv preprint arXiv:1907.02050, 2019
82019
Stdp learning of image features with spiking neural networks
DJ Saunders, HT Siegelmann, R Kozma, M Ruszinkó
IEEE/INNS International Joint Conference on Neural Networks (IJCNN2018)(Rio …, 2018
42018
Minibatch processing for speed-up and scalability of spiking neural network simulation
DJ Saunders, C Sigrist, K Chaney, R Kozma, HT Siegelmann
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
32020
Minibatch processing in spiking neural networks
DJ Saunders, C Sigrist, K Chaney, R Kozma, HT Siegelmann
arXiv preprint arXiv:1909.02549, 2019
32019
A Survey and Discussion of Memcomputing Machines
D Saunders
arXiv preprint arXiv:1704.06145, 2017
12017
Unsupervised Machine Learning to Teach Fluid Dynamicists to Think in 15 Dimensions
SM Kops, DJ Saunders, EA Rietman, GD Portwood
arXiv preprint arXiv:1907.10035, 2019
2019
Investigating the Power of Circuits with Gates
DJ Saunders
arXiv preprint arXiv:1810.05603, 2018
2018
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