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1Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning
J. Richards, R. Huser, E. Bevacqua, and J. Zscheischler. Artificial Intelligence for the Earth Systems, (October 2023)
8 months ago by @scadsfct
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Extreme
Mediterranean
Spatiotemporal
Statistical
Trends
Wildfires
zno
learning
deep
ExtremeMediterraneanSpatiotemporalStatisticalTrendsWildfiresznolearningdeep
(0)
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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)
8 months ago by @scadsfct
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Distance
Linear
Metric
Noisy_Labels
imported
yaff
learning
DistanceLinearMetricNoisy_Labelsimportedyafflearning
(0)
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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)
8 months ago by @scadsfct
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BioDeepfuse
RNA
classification
deep
extraction
feature
learning
non-coding
zno
BioDeepfuseRNAclassificationdeepextractionfeaturelearningnon-codingzno
(0)
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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)
7 months 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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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)
7 months ago by @scadsfct
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Complexity
Computational
Consciousness
Information
Locked-In
Measures
Modeling
Neuroscience
Prediction
Predictive
Processing
Signal
Syndrome
Theory
Training
algorithms
and
data
learning
modeling
models
processing
zno
machine
ComplexityComputationalConsciousnessInformationLocked-InMeasuresModelingNeurosciencePredictionPredictiveProcessingSignalSyndromeTheoryTrainingalgorithmsanddatalearningmodelingmodelsprocessingznomachine
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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)
7 months ago by @scadsfct
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algorithms
learning
networks
neural
neurological
plausible
spiking
xack
algorithmslearningnetworksneuralneurologicalplausiblespikingxack
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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)
7 months ago by @scadsfct
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conscious
hybrid
learning
machine
patient
states
{CLIS}
zno
conscioushybridlearningmachinepatientstates{CLIS}zno
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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)
7 months ago by @scadsfct
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Advantage
Domains
Entity
Recognition
Specific
Transfer
xack
learning
AdvantageDomainsEntityRecognitionSpecificTransferxacklearning
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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)
7 months ago by @scadsfct
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Sim2Real
autonomous
deep
driving
framework
learning
platform-agnostic
reinforcement
xack
Sim2Realautonomousdeepdrivingframeworklearningplatform-agnosticreinforcementxack
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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)
7 months ago by @scadsfct
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best
conic
cost-sensitive
interpretable
learning
machine
meta-learning
mixed-integer
optimization
selection
subset
zno
bestconiccost-sensitiveinterpretablelearningmachinemeta-learningmixed-integeroptimizationselectionsubsetzno
(0)
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1WARC-DL: Scalable Web Archive Processing for Deep Learning
N. Deckers, and M. Potthast. (2022)
7 months ago by @scadsfct
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Archive
Processing
Scalable
WARC-DL
xack
learning
deep
web
ArchiveProcessingScalableWARC-DLxacklearningdeepweb
(0)
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1GradTree: Learning axis-aligned decision trees with gradient descent
S. Marton, S. Lüdtke, C. Bartelt, and H. Stuckenschmidt. (2023)
7 months ago by @scadsfct
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GradTree
axis-aligned
decision
descent
gradient
trees
zno
learning
GradTreeaxis-aligneddecisiondescentgradienttreesznolearning
(0)
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1Manifold learning, the scheme of Laplacian eigenmaps
P. Joharinad, and J. Jost. Mathematics of Data, Springer International Publishing, Cham, (2023)
7 months ago by @scadsfct
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Laplacian
Manifold
eigenmaps
learning
nopdf
LaplacianManifoldeigenmapslearningnopdf
(0)
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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)
7 months ago by @scadsfct
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MLcps
cumulative
learning
machine
performance
yaff
xack
MLcpscumulativelearningmachineperformanceyaffxack
(0)
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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)
7 months ago by @scadsfct
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cancer
grading
histopathology
learning
prostate
self-supervised
topic_lifescience
yaff
cancergradinghistopathologylearningprostateself-supervisedtopic_lifescienceyaff
(0)
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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)
7 months ago by @scadsfct
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Feature
Regularization
Subspace
distance
learning
selection
xack
FeatureRegularizationSubspacedistancelearningselectionxack
(0)
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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)
7 months ago by @scadsfct
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Analysis
Argument
Contrastive
Extractive
Key
Point
Summarization
zno
learning
AnalysisArgumentContrastiveExtractiveKeyPointSummarizationznolearning
(0)
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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)
7 months ago by @scadsfct
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Continual
autoencoder
imported
learning
particle-in-cell
simulation
training
zno
Continualautoencoderimportedlearningparticle-in-cellsimulationtrainingzno
(0)
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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)
7 months ago by @scadsfct
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Bunch
Distribution
Electron
imported
zno
learning
BunchDistributionElectronimportedznolearning
(0)
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1What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation
H. Selder, F. Fischer, P. Kristensson, and A. Fleig. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, page 1–10. ACM, (April 2025)
3 months ago by @scadsfct
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Biomechanical
Design
Function
Reinforcement
Reward
User_Simulation
xack
learning
BiomechanicalDesignFunctionReinforcementRewardUser_Simulationxacklearning
(0)
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1Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning

1Linear Distance Metric Learning with Noisy Labels

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

1On optimizing morphological neural networks for hyperspectral image classification

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

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

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

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

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

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

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

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

1Manifold learning, the scheme of Laplacian eigenmaps

1MLcps: machine learning cumulative performance score for classification problems

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

1Unsupervised feature selection based on variance–covariance subspace distance

1Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

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

1Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

1What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation

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