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1Computation in chemical graph rewriting networks
C. Flamm, D. Merkle, and P. Stadler. Journal of Physics: Complexity, 6 (1): 015014 (March 2025)
a month ago by @scadsfct
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grph
rewriting
chemical
networks
yaff
grphrewritingchemicalnetworksyaff
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1APR-CNN: Convolutional Neural Networks for the Adaptive Particle Representation of Large Microscopy Images
J. Jonsson, B. Cheeseman, and I. Sbalzarini. Transactions on Machine Learning Research, (2025)
a month ago by @scadsfct
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convolutional
neural
images
microscopy
networks
yaff
convolutionalneuralimagesmicroscopynetworksyaff
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1Quantifying synergy and redundancy between networks
A. Luppi, E. Olbrich, C. Finn, L. Suárez, F. Rosas, P. Mediano, and J. Jost. Cell Reports Physical Science, 5 (4): 101892 (April 2024)
9 months ago by @scadsfct
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imported
synergy
Quantifying
redundancy
networks
yaff
importedsynergyQuantifyingredundancynetworksyaff
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1On optimizing morphological neural networks for hyperspectral image classification
M. Kukushkin, M. Bogdan, and T. Schmid. Sixteenth International Conference on Machine Vision (ICMV 2023), 13072, page 1307202. International Society for Optics and Photonics, SPIE, (2024)
8 months ago by @scadsfct
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image
sensing
morphological
morphology
deep
neuronal
learning
networks
classification
remote
mathematical
nopdf
computer
hyperspectral
vision
imagesensingmorphologicalmorphologydeepneuronallearningnetworksclassificationremotemathematicalnopdfcomputerhyperspectralvision
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1Robust Reconstruction of the Void Fraction from Noisy Magnetic Flux Density Using Invertible Neural Networks
N. Kumar, L. Krause, T. Wondrak, S. Eckert, K. Eckert, and S. Gumhold. Sensors, (2024)
10 months ago by @scadsfct
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Noisy
Density
Invertible
Magnetic
neural
Reconstruction
xack
Flux
Fraction
Void
topic_visualcomputing
networks
NoisyDensityInvertibleMagneticneuralReconstructionxackFluxFractionVoidtopic_visualcomputingnetworks
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1Inadequacy of common stochastic neural networks for reliable clinical decision support
A. Lindenmeyer, M. Blattmann, S. Franke, T. Neumuth, and D. Schneider. (2024)
9 months ago by @scadsfct
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reliable
clinical
decision
neural
Inadequacy
stochastic
xack
support
networks
reliableclinicaldecisionneuralInadequacystochasticxacksupportnetworks
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1NaviCenta - The disease map for placental research
J. Scheel, M. Hoch, M. Wolfien, and S. Gupta. Placenta, (November 2023)
12 months ago by @scadsfct
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biology
Molecular
Omics
topic_lifescience
Systems
map
interaction
analysis
networks
yaff
integration
biologyMolecularOmicstopic_lifescienceSystemsmapinteractionanalysisnetworksyaffintegration
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1Clustering systems of phylogenetic networks
M. Hellmuth, D. Schaller, and P. Stadler. Theory in Biosciences, 142 (4): 301–358 (August 2023)
9 months ago by @scadsfct
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systems
Clustering
phylogenetic
zno
networks
systemsClusteringphylogeneticznonetworks
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1Individual modelling of haematotoxicity with NARX neural networks: A knowledge transfer approach
M. Steinacker, Y. Kheifetz, and M. Scholz. Heliyon, 9 (7): e17890 (July 2023)
12 months ago by @scadsfct
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neural
Recurrent
learning
medicine
unit_transfer
networks
System
identification
Precision
Haematopoiesis
topic_mathfoundation
Transfer
topic_neuroinspired
yaff
neuralRecurrentlearningmedicineunit_transfernetworksSystemidentificationPrecisionHaematopoiesistopic_mathfoundationTransfertopic_neuroinspiredyaff
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1Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network
A. Iporre-Rivas, D. Saur, K. Rohr, G. Scheuermann, and C. Gillmann. J. Med. Imaging (Bellingham), 10 (4): 044502 (July 2023)
12 months ago by @scadsfct
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imaging
stroke
medical
neural
machine
prediction
learning
multi-modal
topic_visualcomputing
networks
graph
yaff
imagingstrokemedicalneuralmachinepredictionlearningmulti-modaltopic_visualcomputingnetworksgraphyaff
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1Transcriptomic signatures reveal a shift towards an anti-inflammatory gene expression profile but also the induction of type I and type II interferon signaling networks through aryl hydrocarbon receptor activation in murine macrophages
J. Schmidt, J. Haupt, S. Riemschneider, C. Kämpf, D. Löffler, C. Blumert, K. Reiche, U. Koehl, S. Kalkhof, and J. Lehmann. Frontiers in Immunology, (May 2023)
9 months ago by @scadsfct
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signaling
through
gene
profile
expression
hydrocarbon
networks
aryl
interferon
signatures
induction
murine
receptor
anti-inflammatory
zno
macrophages
Transcriptomic
activation
signalingthroughgeneprofileexpressionhydrocarbonnetworksarylinterferonsignaturesinductionmurinereceptoranti-inflammatoryznomacrophagesTranscriptomicactivation
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1Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images
M. Tkachenko, C. Chalopin, B. Jansen-Winkeln, T. Neumuth, I. Gockel, and M. Maktabi. Cancers (Basel), (April 2023)
12 months ago by @scadsfct
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convolutional
imaging
cancer
pre-processing
learning
networks
classification
colorectal
median
machine
hyperspectral
topic_lifescience
post-processing
filter
yaff
convolutionalimagingcancerpre-processinglearningnetworksclassificationcolorectalmedianmachinehyperspectraltopic_lifesciencepost-processingfilteryaff
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1Every atom-atom map can be explained by electron pushing diagrams
C. Flamm, S. Müller, and P. Stadler. (2023)
9 months ago by @scadsfct
show all tags
92E10
sciences
Molecular
FOS
Mathematics
Biological
05C92
Combinatorics
networks
yaff
92E10sciencesMolecularFOSMathematicsBiological05C92Combinatoricsnetworksyaff
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2Outlying aspect mining via sum-product networks
S. Lüdtke, C. Bartelt, and H. Stuckenschmidt. Advances in Knowledge Discovery and Data Mining, Springer Nature Switzerland, Cham, (2023)
8 months ago by @scadsfct
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Outlying
aspect
xack
networks
sum-product
Outlyingaspectxacknetworkssum-product
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1ChatIDS: Explainable Cybersecurity Using Generative AI
V. Jüttner, M. Grimmer, and E. Buchmann. (2023)
8 months ago by @scadsfct
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Intrusion
ChatGPT
Detection
networks
yaff
IntrusionChatGPTDetectionnetworksyaff
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1Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse
M. Bogdan. XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja), Servizo de Publicacións da UDC, (September 2022)
8 months ago by @scadsfct
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neural
algorithms
spiking
xack
learning
plausible
networks
neurological
neuralalgorithmsspikingxacklearningplausiblenetworksneurological
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1Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology
N. Ghaffari Laleh, H. Muti, C. Loeffler, A. Echle, O. Saldanha, F. Mahmood, M. Lu, C. Trautwein, R. Langer, B. Dislich and 13 other author(s). Med. Image Anal., 79 (102474): 102474 (July 2022)
12 months ago by @scadsfct
show all tags
Convolutional
pathology
Multiple-Instance
deep
neural
learning
networks
Weakly-supervised
intelligence
Learning;
artificial
transformers;
topic_lifescience
Vision
zno
Computational
ConvolutionalpathologyMultiple-InstancedeepneurallearningnetworksWeakly-supervisedintelligenceLearning;artificialtransformers;topic_lifescienceVisionznoComputational
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1Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review
L. Schneider, S. Laiouar-Pedari, S. Kuntz, E. Krieghoff-Henning, A. Hekler, J. Kather, T. Gaiser, S. Fröhling, and T. Brinker. Eur. J. Cancer, (January 2022)
12 months ago by @scadsfct
show all tags
Convolutional
identification
Cancer
Biomarker
Multimodal
neural
Omics
fusion
topic_lifescience
zno
networks
ConvolutionalidentificationCancerBiomarkerMultimodalneuralOmicsfusiontopic_lifescienceznonetworks
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1Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs
C. Xu, F. Su, and J. Lehmann. (2022)
8 months ago by @scadsfct
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Entity
Graph
Alignment
graphs
neural
Time-aware
Temporal
networks
Knowledge
yaff
EntityGraphAlignmentgraphsneuralTime-awareTemporalnetworksKnowledgeyaff
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1Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks
A. Marcolongo, M. Vladymyrov, S. Lienert, N. Peleg, S. Haug, and J. Zscheischler. Environmental Data Science, (2022)
9 months ago by @scadsfct
show all tags
Convolutional
Predicting
low
gross
production
neural
data
zno
primary
networks
weather
ConvolutionalPredictinglowgrossproductionneuraldataznoprimarynetworksweather
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publications (hide)25
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1Computation in chemical graph rewriting networks

1APR-CNN: Convolutional Neural Networks for the Adaptive Particle Representation of Large Microscopy Images

1Quantifying synergy and redundancy between networks

1On optimizing morphological neural networks for hyperspectral image classification

1Robust Reconstruction of the Void Fraction from Noisy Magnetic Flux Density Using Invertible Neural Networks

1Inadequacy of common stochastic neural networks for reliable clinical decision support

1NaviCenta - The disease map for placental research

1Clustering systems of phylogenetic networks

1Individual modelling of haematotoxicity with NARX neural networks: A knowledge transfer approach

1Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network

1Transcriptomic signatures reveal a shift towards an anti-inflammatory gene expression profile but also the induction of type I and type II interferon signaling networks through aryl hydrocarbon receptor activation in murine macrophages

1Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images

1Every atom-atom map can be explained by electron pushing diagrams

2Outlying aspect mining via sum-product networks

1ChatIDS: Explainable Cybersecurity Using Generative AI

1Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse

1Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology

1Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review

1Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs

1Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks

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