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1Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
A. Willmann, J. Cabadağ, Y. Chang, R. Pausch, A. Ghaith, A. Debus, A. Irman, M. Bussmann, U. Schramm, and N. Hoffmann. (2023)
a month ago by @scadsfct
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Bunch
Distribution
Electron
Learning
Zno
imported
BunchDistributionElectronLearningZnoimported
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1Continual learning autoencoder training for a particle-in-cell simulation via streaming
P. Stiller, V. Makdani, F. Pöschel, R. Pausch, A. Debus, M. Bussmann, and N. Hoffmann. (2022)
a month ago by @scadsfct
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Continual
Zno
autoencoder
imported
learning
particle-in-cell
simulation
training
ContinualZnoautoencoderimportedlearningparticle-in-cellsimulationtraining
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1Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
M. Alshomary, T. Gurcke, S. Syed, P. Heinisch, M. Spliethöver, P. Cimiano, M. Potthast, and H. Wachsmuth. 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP, page 184--189. Association for Computational Linguistics, (November 2021)
a month ago by @scadsfct
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Analysis
Argument
Contrastive
Extractive
Key
Learning
Point
Summarization
Zno
AnalysisArgumentContrastiveExtractiveKeyLearningPointSummarizationZno
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1Unsupervised feature selection based on variance–covariance subspace distance
S. Karami, F. Saberi-Movahed, P. Tiwari, P. Marttinen, and S. Vahdati. Neural Networks, (2023)
a month ago by @scadsfct
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Feature
Regularization
Subspace
Xack
distance
learning
selection
FeatureRegularizationSubspaceXackdistancelearningselection
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2Self-supervised learning in histopathology: New perspectives for prostate cancer grading
M. Bauer, and C. Augenstein. Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, (2024)
a month ago by @scadsfct
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Yaff
cancer
grading
histopathology
learning
prostate
self-supervised
topic_lifescience
Yaffcancergradinghistopathologylearningprostateself-supervisedtopic_lifescience
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1MLcps: machine learning cumulative performance score for classification problems
A. Akshay, M. Abedi, N. Shekarchizadeh, F. Burkhard, M. Katoch, A. Bigger-Allen, R. Adam, K. Monastyrskaya, and A. Gheinani. GigaScience, (December 2023)
a month ago by @scadsfct
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MLcps
Xack
Yaff
cumulative
learning
machine
performance
MLcpsXackYaffcumulativelearningmachineperformance
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1Manifold learning, the scheme of Laplacian eigenmaps
P. Joharinad, and J. Jost. Mathematics of Data, Springer International Publishing, Cham, (2023)
a month ago by @scadsfct
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Laplacian
Manifold
eigenmaps
learning
nopdf
LaplacianManifoldeigenmapslearningnopdf
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1GradTree: Learning axis-aligned decision trees with gradient descent
S. Marton, S. Lüdtke, C. Bartelt, and H. Stuckenschmidt. (2023)
a month ago by @scadsfct
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GradTree
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trees
GradTreeLearningZnoaxis-aligneddecisiondescentgradienttrees
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1WARC-DL: Scalable Web Archive Processing for Deep Learning
N. Deckers, and M. Potthast. (2022)
a month ago by @scadsfct
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Archive
Deep
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WARC-DL
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Xack
ArchiveDeepLearningProcessingScalableWARC-DLWebXack
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1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective
R. Knauer, and E. Rodner. KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI, Berlin, Germany, September 26--29, 2023, Proceedings, page 114--129. Berlin, Heidelberg, Springer-Verlag, (2023)
a month ago by @scadsfct
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Zno
best
conic
cost-sensitive
interpretable
learning
machine
meta-learning
mixed-integer
optimization
selection
subset
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1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving
D. Li, and O. Okhrin. Commun Eng, 3 (1): 147 (October 2024)
a month ago by @scadsfct
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Sim2Real
Xack
autonomous
deep
driving
framework
learning
platform-agnostic
reinforcement
Sim2RealXackautonomousdeepdrivingframeworklearningplatform-agnosticreinforcement
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1Named Entity Recognition for Specific Domains - Take Advantage of Transfer Learning
S. Torge, W. Hahn, L. Manjunath, and R. Jäkel. International Journal of Information Science and Technology, (2022)
a month ago by @scadsfct
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Advantage
Domains
Entity
Learning
Recognition
Specific
Transfer
Xack
AdvantageDomainsEntityLearningRecognitionSpecificTransferXack
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1Extendable hybrid approach to detect conscious states in a CLIS patient using machine learning
S. Adama, S. Wu, N. Nicolaou, and M. Bogdan. SNE Simul. Notes Eur., 32 (1): 37--45 (2022)
a month ago by @scadsfct
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Zno
conscious
hybrid
learning
machine
patient
states
{CLIS}
Znoconscioushybridlearningmachinepatientstates{CLIS}
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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)
a month ago by @scadsfct
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Learning
Xack
algorithms
learning
networks
neural
neurological
plausible
spiking
LearningXackalgorithmslearningnetworksneuralneurologicalplausiblespiking
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1Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient
O. Kirsten, M. Bogdan, and S. Adama. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), page 37-41. (2023)
a month ago by @scadsfct
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Complexity
Computational
Consciousness
Information
Learning
Locked-In
Machine
Measures
Modeling
Neuroscience
Prediction
Predictive
Processing
Signal
Syndrome
Theory
Training
Zno
algorithms
and
data
learning
modeling
models
processing
ComplexityComputationalConsciousnessInformationLearningLocked-InMachineMeasuresModelingNeurosciencePredictionPredictiveProcessingSignalSyndromeTheoryTrainingZnoalgorithmsanddatalearningmodelingmodelsprocessing
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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)
a month ago by @scadsfct
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classification
computer
deep
hyperspectral
image
learning
mathematical
morphological
morphology
networks
neuronal
nopdf
remote
sensing
vision
classificationcomputerdeephyperspectralimagelearningmathematicalmorphologicalmorphologynetworksneuronalnopdfremotesensingvision
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1BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
A. Avila Santos, B. de Almeida, R. Bonidia, P. Stadler, P. Stefanic, I. Mandic-Mulec, U. Rocha, D. Sanches, and A. de Carvalho. RNA Biology, 21 (1): 410–421 (March 2024)
2 months ago by @scadsfct
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BioDeepfuse
RNA
Zno
classification
deep
extraction
feature
learning
non-coding
BioDeepfuseRNAZnoclassificationdeepextractionfeaturelearningnon-coding
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1Linear Distance Metric Learning with Noisy Labels
M. Alishahi, A. Little, and J. Phillips. Journal of Machine Learning Research, 25 (121): 1--53 (2024)
2 months ago by @scadsfct
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Distance
Learning
Linear
Metric
Noisy_Labels
Yaff
imported
DistanceLearningLinearMetricNoisy_LabelsYaffimported
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publications (hide)43
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1Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

1Continual learning autoencoder training for a particle-in-cell simulation via streaming

1Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

1Unsupervised feature selection based on variance–covariance subspace distance

2Self-supervised learning in histopathology: New perspectives for prostate cancer grading

1MLcps: machine learning cumulative performance score for classification problems

1Manifold learning, the scheme of Laplacian eigenmaps

1GradTree: Learning axis-aligned decision trees with gradient descent

1WARC-DL: Scalable Web Archive Processing for Deep Learning

1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective

1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving

1Named Entity Recognition for Specific Domains - Take Advantage of Transfer Learning

1Extendable hybrid approach to detect conscious states in a CLIS patient using machine learning

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

1Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient

1On optimizing morphological neural networks for hyperspectral image classification

1BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

1Linear Distance Metric Learning with Noisy Labels

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