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1Global Sensor Networks
http://sourceforge.net/apps/trac/gsn/wiki
12 лет назад , @becker
sensors
network
sensorsnetwork
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2Debugging Neural Networks: A Checklist – Engineering@Semantics3
https://engineering.semantics3.com/debugging-neural-networks-a-checklist-ca52e11151ec
7 лет назад , @becker
debug
optimization
neural
optimize
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nn
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1Generative Adversarial Nets in TensorFlow - Agustinus Kristiadi's Blog
https://wiseodd.github.io/techblog/2016/09/17/gan-tensorflow/
7 лет назад , @becker
code
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tensorflow
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1https://scholar.googleusercontent.com/scholar.bib?q=info:vegxY8zEn-EJ:scholar.google.com/&output=citation&scisdr=CgUqPzX2ELPhtbXua4o:AAGBfm0AAAAAXlbrc4r8g9aX1vJ_7ANfvGsZjz2luRyR&scisig=AAGBfm0AAAAAXlbrc2pK3JcRojAQtKHudSF69nVueJ6A&scisf=4&ct=citation&cd=0&hl=en
https://scholar.googleusercontent.com/scholar.bib?q=info:vegxY8zEn-EJ:scholar.google.com/&output=citation&scisdr=CgUqPzX2ELPhtbXua4o:AAGBfm0AAAAAXlbrc4r8g9aX1vJ_7ANfvGsZjz2luRyR&scisig=AAGBfm0AAAAAXlbrc2pK3JcRojAQtKHudSF69nVueJ6A&scisf=4&ct=citation&cd=0&hl=en
5 лет назад , @becker
bayesian
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1optimization - What causes sudden drops in training/test errors when training a neural network? - Cross Validated
https://stats.stackexchange.com/questions/300839/what-causes-sudden-drops-in-training-test-errors-when-training-a-neural-network
4 лет назад , @becker
stagnant
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1IraKorshunova/bruno: a deep recurrent model for exchangeable data
https://github.com/IraKorshunova/bruno
6 лет назад , @becker
bayesian
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1CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 - YouTube
https://www.youtube.com/watch?v=i94OvYb6noo
5 лет назад , @becker
youtube
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weight
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1Your Beginner Guide to Roam Research — Keep Productive
https://www.keepproductive.com/blog/roam-research-guide
4 лет назад , @becker
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1Understanding Convolutions on Graphs
https://distill.pub/2021/understanding-gnns/
3 лет назад , @becker
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1calico/scBasset: Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.
https://github.com/calico/scBasset
2 лет назад , @becker
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1A Visual Guide to Using BERT for the First Time – Jay Alammar – Visualizing machine learning one concept at a time.
https://jalammar.github.io/a-visual-guide-to-using-bert-for-the-first-time/
4 лет назад , @becker
nlp
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1scwatts/fastspar: Rapid and scalable correlation estimation for compositional data
https://github.com/scwatts/fastspar
2 лет назад , @becker
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1Neural network configuration
https://twitter.com/karpathy/status/1528808361558306817?t=DcAepTf_tNH1FP-wEjzWzQ&s=19
2 years ago by @becker
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2rasbt/python-machine-learning-book-2nd-edition: The "Python Machine Learning (2nd edition)" book code repository and info resource
https://github.com/rasbt/python-machine-learning-book-2nd-edition#whats-new-in-the-second-edition-from-the-first-edition
7 years ago by @becker
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jupyter
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machine
ipython
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learning
network
networks
ml
nn
jupytercodeneuralbookmachineipythontutoriallearningnetworknetworksmlnn
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1dnsmasq: how to assign hostnames
https://unix.stackexchange.com/questions/16890/how-to-make-a-machine-accessible-from-the-lan-using-its-hostname
7 years ago by @becker
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raspberry
access
hosts
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network
ap
hostapd
point
dnsmasq
hostname
hostnames
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pi
raspberryaccesshostsdnsnetworkaphostapdpointdnsmasqhostnamehostnameshostpi
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1I can I stop this annoying addition of all my network printers : Ubuntu
https://www.reddit.com/r/Ubuntu/comments/7xjinc/i_can_i_stop_this_annoying_addition_of_all_my/
5 years ago by @becker
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linux
print
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list
linuxprintprintersprinterdiscoverycupskdenetworklist
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1live ssh network throughput test Using ssh, yes
https://www.commandlinefu.com/commands/view/4434/live-ssh-network-throughput-test
5 years ago by @becker
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linux
pv
throughput
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1lecture2.pdf
http://people.csail.mit.edu/dsontag/courses/pgm12/slides/lecture2.pdf
7 years ago by @becker
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graphical
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1(6) 8 AI Technologies that ain't Neural Networks | LinkedIn
https://www.linkedin.com/pulse/8-ai-technologies-aint-neural-networks-brandon-wirtz/
7 years ago by @becker
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technologies
neural
ai
technology
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notechnologiesneuralaitechnologynetworknon
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1What is amortized variational inference? - Quora
https://www.quora.com/What-is-amortized-variational-inference#:~:text=Amortizing%20Posterior%20Inference,of%20the%20approximate%20posterior%20distribution.
5 years ago by @becker
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1DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture
A. Sharma, E. Vans, D. Shigemizu, K. Boroevich, and T. Tsunoda. Scientific reports, 9 (1): 1--7 (2019)
5 years ago by @becker
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cytometry
nalab
tsne
cnn
dimensionality
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deep
neural
rna
learning
network
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cytometrynalabtsnecnndimensionalityconvoluationaldeepneuralrnalearningnetworkumapembeddingreductioninsightcytof
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1Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
M. Raissi, P. Perdikaris, and G. Karniadakis. Journal of Computational physics, (2019)
2 years ago by @becker
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equation
pde
citedby:scholar:count:3855
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network
citedby:scholar:timestamp:2022-11-11
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nn
equationpdecitedby:scholar:count:3855neuralround1partialnetworkcitedby:scholar:timestamp:2022-11-11differentialnn
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1Genetic and environmental perturbations lead to regulatory decoherence
A. Lea, M. Subramaniam, A. Ko, T. Lehtimäki, E. Raitoharju, M. Kähönen, I. Seppälä, N. Mononen, O. Raitakari, M. Ala-Korpela and 1 other author(s). Elife, (2019)
2 years ago by @becker
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genetic
decoherence
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cordis
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citedby:scholar:timestamp:2022-7-28
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geneticdecoherencecoherencegenecordiscorrelationregulatorycitedby:scholar:timestamp:2022-7-28citedby:scholar:count:28networknetworksdifferential
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1Wasserstein GAN-Based Small-Sample Augmentation for New-Generation Artificial Intelligence: A Case Study of Cancer-Staging Data in Biology
Y. Liu, Y. Zhou, X. Liu, F. Dong, C. Wang, and Z. Wang. Engineering, 5 (1): 156 - 163 (2019)
5 years ago by @becker
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gan
neural
adversarial
data
afcs
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augmentation
network
generative
nn
ganneuraladversarialdataafcsmodelaugmentationnetworkgenerativenn
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2Deep learning for inferring gene relationships from single-cell expression data
Y. Yuan, and Z. Bar-Joseph. Proceedings of the National Academy of Sciences, 116 (52): 27151--27158 (2019)
4 years ago by @becker
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cnn
gene
deep
neural
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nn
single
cell
cnngenedeepneuralpredictionlearningnetworknnsinglecell
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2Estimating sample-specific regulatory networks
M. Kuijjer, M. Tung, G. Yuan, J. Quackenbush, and K. Glass. Iscience, (2019)
4 years ago by @becker
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estimation
disruption
lioness
citedby:scholar:timestamp:2020-7-16
citedby:scholar:count:25
correlation
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p21
estimationdisruptionlionesscitedby:scholar:timestamp:2020-7-16citedby:scholar:count:25correlationrelatedworknetworksamplesinglep21
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2One-class adversarial nets for fraud detection
P. Zheng, S. Yuan, X. Wu, J. Li, and A. Lu. Proceedings of the AAAI Conference on Artificial Intelligence, 33, page 1286--1293. (2019)
4 years ago by @becker
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citedby:scholar:count:41
citedby:scholar:timestamp:2021-2-14
detection
one
neural
adversarial
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m:
m:id:test1:node
network
m:id:test1:coordinate:x:193.69368743896484
p21
m:id:test1:coordinate:y:66.44144439697266
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class
relatedwork
net
citedby:scholar:count:41citedby:scholar:timestamp:2021-2-14detectiononeneuraladversarialoutlierm:m:id:test1:nodenetworkm:id:test1:coordinate:x:193.69368743896484p21m:id:test1:coordinate:y:66.44144439697266fraudclassrelatedworknet
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1BioNetStat: a tool for biological networks differential analysis
V. Jardim, S. Santos, A. Fujita, and M. Buckeridge. Frontiers in genetics, (2019)
2 years ago by @becker
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citedby:scholar:count:13
citedby:scholar:timestamp:2022-4-27
analysis
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paper:fastcor
citedby:scholar:count:13citedby:scholar:timestamp:2022-4-27analysisnetworkdifferentialpaper:fastcor
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2Relational inductive biases, deep learning, and graph networks
P. Battaglia, J. Hamrick, V. Bapst, A. Sanchez-Gonzalez, V. Zambaldi, M. Malinowski, A. Tacchetti, D. Raposo, A. Santoro, R. Faulkner and 1 other author(s). arXiv preprint arXiv:1806.01261, (2018)
4 years ago by @becker
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citedby:scholar:count:761
citedby:scholar:timestamp:2020-9-18
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bayesianinductivedeepneurallearningnetworknetworksgraphcitedby:scholar:count:761citedby:scholar:timestamp:2020-9-18bayesbiasrelational
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1OmicsMapNet: Transforming omics data to take advantage of Deep Convolutional Neural Network for discovery
S. Ma, and Z. Zhang. arXiv preprint arXiv:1804.05283, (2018)
4 years ago by @becker
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cnn
convoluational
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omics
citedby:scholar:count:5
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citedby:scholar:timestamp:2020-8-31
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1Global Sensor Networks

2Debugging Neural Networks: A Checklist – Engineering@Semantics3

1Generative Adversarial Nets in TensorFlow - Agustinus Kristiadi's Blog

1https://scholar.googleusercontent.com/scholar.bib?q=info:vegxY8zEn-EJ:scholar.google.com/&output=citation&scisdr=CgUqPzX2ELPhtbXua4o:AAGBfm0AAAAAXlbrc4r8g9aX1vJ_7ANfvGsZjz2luRyR&scisig=AAGBfm0AAAAAXlbrc2pK3JcRojAQtKHudSF69nVueJ6A&scisf=4&ct=citation&cd=0&hl=en

1optimization - What causes sudden drops in training/test errors when training a neural network? - Cross Validated

1IraKorshunova/bruno: a deep recurrent model for exchangeable data

1CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 - YouTube

1Your Beginner Guide to Roam Research — Keep Productive

1Understanding Convolutions on Graphs

1calico/scBasset: Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.

1A Visual Guide to Using BERT for the First Time – Jay Alammar – Visualizing machine learning one concept at a time.

1scwatts/fastspar: Rapid and scalable correlation estimation for compositional data

1Neural network configuration

2rasbt/python-machine-learning-book-2nd-edition: The "Python Machine Learning (2nd edition)" book code repository and info resource

1dnsmasq: how to assign hostnames

1I can I stop this annoying addition of all my network printers : Ubuntu

1live ssh network throughput test Using ssh, yes

1lecture2.pdf

1(6) 8 AI Technologies that ain't Neural Networks | LinkedIn

1What is amortized variational inference? - Quora

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1DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture

1Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

1Genetic and environmental perturbations lead to regulatory decoherence

1Wasserstein GAN-Based Small-Sample Augmentation for New-Generation Artificial Intelligence: A Case Study of Cancer-Staging Data in Biology

2Deep learning for inferring gene relationships from single-cell expression data

2Estimating sample-specific regulatory networks

2One-class adversarial nets for fraud detection

1BioNetStat: a tool for biological networks differential analysis

2Relational inductive biases, deep learning, and graph networks

1OmicsMapNet: Transforming omics data to take advantage of Deep Convolutional Neural Network for discovery

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