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1calico/scBasset: Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.
https://github.com/calico/scBasset
2 years ago by @becker
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convolutional
code
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github
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atac
network
atacseq
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seq
convolutionalcodecnngithubneuralatacnetworkatacseqclassificationseq
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1WangYueFt/dgcnn
https://github.com/WangYueFt/dgcnn
4 years ago by @becker
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github
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2Latent graph neural networks: Manifold learning 2.0? | by Michael Bronstein | Sep, 2020 | Towards Data Science
https://towardsdatascience.com/manifold-learning-2-99a25eeb677d
4 years ago by @becker
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convolutional
cnn
functional
disruption
pointnet
neural
network
graph
cell
correlation
interaction
dynamic
nn
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convolutionalcnnfunctionaldisruptionpointnetneuralnetworkgraphcellcorrelationinteractiondynamicnnsingle
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1leftthomas/DGCNN: A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"
https://github.com/leftthomas/DGCNN
4 years ago by @becker
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cloud
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2GitHub - facebookresearch/detectron2: Detectron2 is FAIR's next-generation platform for object detection and segmentation.
https://github.com/facebookresearch/detectron2
4 years ago by @hotho
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cnn
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imagecnndeeplearningsegmentationnetwork
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1niftynet
https://niftynet.io/
5 years ago by @nosebrain
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cnn
medical
niftynet
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flow
cnnmedicalniftynetimagestensorflow
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1CS231n Convolutional Neural Networks for Visual Recognition
Course materials and notes for Stanford class CS231n: Convolutional Neural Networks for Visual Recognition.
5 years ago by @nosebrain
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1Bayesian Neural Network Series Post 2: Background Knowledge
https://medium.com/neuralspace/bayesian-neural-network-series-post-2-background-knowledge-fdec6ac62d43
5 years ago by @becker
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1Convolutional neural networks for artistic style transfer — Harish Narayanan
https://harishnarayanan.org/writing/artistic-style-transfer/
5 years ago by @becker
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cnn
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1stanford-cs-230-deep-learning/cheatsheet-convolutional-neural-networks.pdf at master · afshinea/stanford-cs-230-deep-learning
https://github.com/afshinea/stanford-cs-230-deep-learning/blob/master/en/cheatsheet-convolutional-neural-networks.pdf
6 years ago by @thoni
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cnn
neuralnet
cheatsheet
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1A Review of Deep Contextualized Word Representations (Peters+, 2018)
https://www.slideshare.net/shuntaroy/a-review-of-deep-contextualized-word-representations-peters-2018
6 years ago by @schwemmlein
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presentation
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bilm
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nlppresentationcnndeepallennlpembeddingselmobilmlearninglstmnaaclword
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6MNIST handwritten digit database, Yann LeCun, Corinna Cortes and Chris Burges
http://yann.lecun.com/exdb/mnist/
6 years ago by @nosebrain
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cnn
leaderboard
mnist
cnnleaderboardmnist
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2Relation Extraction using Deep learning(CNN)
The code is an implementation of the paper http://www.aclweb.org/anthology/C14-1220 using tensorflow.
7 years ago by @schwemmlein
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github
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python
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extraction
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1Convolution neural network for relation extraction between two given entities
The CNN architecture implemented is inspired be Nguyen et al. 2015
7 years ago by @schwemmlein
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github
python
neural
relation
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extraction
codecnngithubpythonneuralrelationnetworkextraction
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1Neural Relation Extraction, including CNN, PCNN, CNN+ATT, PCNN+ATT
In this project, we provide our implementations of CNN [Zeng et al., 2014] and PCNN [Zeng et al.,2015] and their extended version with sentence-level attention scheme [Lin et al., 2016] .
7 years ago by @schwemmlein
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extraction
codec++cnngithubneuralrelationnetworkextraction
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1Convolutional Neural Network for Multi-label Multi-instance Relation Extraction in Tensorflow
Convolutional Neural Network for Relation Extraction
7 years ago by @schwemmlein
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github
tensorflow
python
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codecnngithubtensorflowpythonneuralrelationextractionnetworks
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1karpathy/neuraltalk: NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
https://github.com/karpathy/neuraltalk
7 years ago by @nosebrain
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rnn
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neurotalk
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imagernncodecnnneurotalkpythonpaper:neural_tagcaption
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1ritchieng/NumNum: Multi-digit prediction from Google Street's images using deep CNN with TensorFlow, OpenCV and Python.
NumNum - Multi-digit prediction from Google Street's images using deep CNN with TensorFlow, OpenCV and Python.
7 years ago by @nosebrain
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cnn
tensorflow
numnum
prediction
digit
multi
cnntensorflownumnumpredictiondigitmulti
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2Neural Network Architectures
https://culurciello.github.io/tech/2016/06/04/nets.html
8 years ago by @dallmann
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overview
cnn
deep_learning
overviewcnndeep_learning
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4ConvNetJS: Deep Learning in your browser
http://cs.stanford.edu/people/karpathy/convnetjs/
8 years ago by @nosebrain
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lecture:data-mining
cnn
deep
learning
javascript
lecture:data-miningcnndeeplearningjavascript
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publications (hide)83
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2Supertml: Two-dimensional word embedding for the precognition on structured tabular data
B. Sun, L. Yang, W. Zhang, M. Lin, P. Dong, C. Young, and J. Dong. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, page 0--0. (2019)
3 years ago by @becker
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citedby:scholar:timestamp:2021-4-24
cnn
neural
data
citedby:scholar:count:6
tabular
network
nn
citedby:scholar:timestamp:2021-4-24cnnneuraldatacitedby:scholar:count:6tabularnetworknn
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3Recurrent Convolutional Neural Network for Sequential Recommendation
C. Xu, P. Zhao, Y. Liu, J. Xu, V. S.Sheng, Z. Cui, X. Zhou, and H. Xiong. The World Wide Web Conference, page 3398–3404. New York, NY, USA, Association for Computing Machinery, (2019)
4 years ago by @dallmann
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sequential_item
rnn
cnn
recommendation
deep_learning
sequential_itemrnncnnrecommendationdeep_learning
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1Dynamic graph cnn for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. Sarma, M. Bronstein, and J. Solomon. Acm Transactions On Graphics (tog), 38 (5): 1--12 (2019)
4 years ago by @becker
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cnn
neural
network
graph
classification
cell
citedby:scholar:count:674
point
cloud
citedby:scholar:timestamp:2020-9-10
dynamic
nn
single
cnnneuralnetworkgraphclassificationcellcitedby:scholar:count:674pointcloudcitedby:scholar:timestamp:2020-9-10dynamicnnsingle
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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
deep
neural
tree
network
multi
omics
citedby:scholar:count:5
multiomics
citedby:scholar:timestamp:2020-8-31
map
nn
cnnconvoluationaldeepneuraltreenetworkmultiomicscitedby:scholar:count:5multiomicscitedby:scholar:timestamp:2020-8-31mapnn
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1Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer
G. Jurman, V. Maggio, D. Fioravanti, Y. Giarratano, I. Landi, M. Francescatto, C. Agostinelli, M. Chierici, M. De Domenico, and C. Furlanello. arXiv preprint arXiv:1710.05918, (2017)
4 years ago by @becker
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convolutional
cnn
neural
network
graph
multi
structure
citedby:scholar:count:2
omics
background
multiomics
citedby:scholar:timestamp:2020-8-31
knowledge
convolutionalcnnneuralnetworkgraphmultistructurecitedby:scholar:count:2omicsbackgroundmultiomicscitedby:scholar:timestamp:2020-8-31knowledge
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3Recurrent Convolutional Neural Network for Sequential Recommendation
C. Xu, P. Zhao, Y. Liu, J. Xu, V. S.Sheng, Z. Cui, X. Zhou, and H. Xiong. The World Wide Web Conference, page 3398–3404. New York, NY, USA, Association for Computing Machinery, (2019)
4 years ago by @nosebrain
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rnn
cnn
rcnn
session
recommendation
rnncnnrcnnsessionrecommendation
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3Deep learning for time series classification: a review
H. Ismail Fawaz, G. Forestier, J. Weber, L. Idoumghar, and P. Muller. Data Mining and Knowledge Discovery, 33 (4): 917--963 (Jul 1, 2019)
4 years ago by @becker
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cnn
deep
neural
series
learning
time
networks
nn
classification
cnndeepneuralserieslearningtimenetworksnnclassification
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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
prediction
learning
network
nn
single
cell
cnngenedeepneuralpredictionlearningnetworknnsinglecell
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4An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
S. Bai, J. Kolter, and V. Koltun. (2018)cite arxiv:1803.01271.
4 years ago by @dallmann
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cnn
sequence_modeling
deep_learning
cnnsequence_modelingdeep_learning
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4Data Augmentation for Time Series Classification using Convolutional Neural Networks
A. Guennec, S. Malinowski, and R. Tavenard. (2016)
4 years ago by @thoni
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convolutional
cnn
data
augmentation
convolutionalcnndataaugmentation
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10Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
J. Tang, and K. Wang. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining - WSDM \textquotesingle18, page 565--573. ACM Press, (2018)
4 years ago by @nosebrain
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caser
cnn
session
recommendation
my:recommendation_framework
casercnnsessionrecommendationmy:recommendation_framework
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11MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images
M. Steininger, K. Kobs, A. Zehe, F. Lautenschlager, M. Becker, and A. Hotho. ACM Transactions on Spatial Algorithms and Systems (TSAS), 6 (3): 1--24 (2020)
4 years ago by @becker
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image
project:bmbf
mapping
myown
cnn
neural
air
network
networks
quality
p21
street
prediction
map
open
imageproject:bmbfmappingmyowncnnneuralairnetworknetworksqualityp21streetpredictionmapopen
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2Deep learning interpretation of echocardiograms
A. Ghorbani, D. Ouyang, A. Abid, B. He, J. Chen, R. Harrington, D. Liang, E. Ashley, and J. Zou. npj Digital Medicine, 3 (1): 10-- (2020)
4 years ago by @becker
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cnn
project
echo
cnnprojectecho
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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)
4 years ago by @becker
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cytometry
nalab
tsne
cnn
dimensionality
convoluational
deep
neural
rna
learning
network
umap
embedding
reduction
insight
cytof
cytometrynalabtsnecnndimensionalityconvoluationaldeepneuralrnalearningnetworkumapembeddingreductioninsightcytof
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1Deep learning of circulating tumour cells
L. Zeune, Y. Boink, G. van Dalum, A. Nanou, S. de Wit, K. Andree, J. Swennenhuis, S. van Gils, L. Terstappen, and C. Brune. Nature Machine Intelligence, (2020)
4 years ago by @becker
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cytometry
nalab
cnn
convoluational
deep
neural
cancer
learning
network
cell
circulating
single
cytof
cytometrynalabcnnconvoluationaldeepneuralcancerlearningnetworkcellcirculatingsinglecytof
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1A robust and interpretable, end-to-end deep learning model for cytometry data
Z. Hu, A. Tang, J. Singh, S. Bhattacharya, and A. Butte. Proceedings of the National Academy of Sciences, 117 (35): 21373--21380 (2020)
4 years ago by @becker
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cytometry
project:bmbf
nalab
cnn
convoluational
deep
neural
learning
network
single
cell
cytof
cytometryproject:bmbfnalabcnnconvoluationaldeepneurallearningnetworksinglecellcytof
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2Detecting Cancer Metastases on Gigapixel Pathology Images
Y. Liu, K. Gadepalli, M. Norouzi, G. Dahl, T. Kohlberger, A. Boyko, S. Venugopalan, A. Timofeev, P. Nelson, G. Corrado and 3 other author(s). (2017)cite arxiv:1703.02442Comment: Fig 1: normal and tumor patches were accidentally reversed - now fixed. Minor grammatical corrections in appendix, section "Image Color Normalization".
5 years ago by @nosebrain
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heathcare
cnn
deep
ai
learning
example
heathcarecnndeepailearningexample
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6Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks
A. Zehe, L. Hettinger, S. Ernst, C. Hauptmann, and A. Hotho. Proceedings of The 13th International Workshop on Semantic Evaluation, Association for Computational Linguistics, (2019)
5 years ago by @hotho
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nlp
news
myown
2019
cnn
semeval
hyperpartisan
nn
nlpnewsmyown2019cnnsemevalhyperpartisannn
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6Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks
A. Zehe, L. Hettinger, S. Ernst, C. Hauptmann, and A. Hotho. Proceedings of The 13th International Workshop on Semantic Evaluation, Association for Computational Linguistics, (2019)
5 years ago by @schwemmlein
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nlp
news
myown
cnn
semeval
hyperpartisan
nn
nlpnewsmyowncnnsemevalhyperpartisannn
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1eXpose: A Character-Level Convolutional Neural Network with Embeddings For Detecting Malicious URLs, File Paths and Registry Keys
J. Saxe, and K. Berlin. (2017)cite arxiv:1702.08568.
5 years ago by @dallmann
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malicious_traffic
cnn
deep_learning
security
malicious_trafficcnndeep_learningsecurity
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