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publications (hide)41
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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
show all tags
driving
framework
platform-agnostic
autonomous
deep
Xack
learning
reinforcement
Sim2Real
drivingframeworkplatform-agnosticautonomousdeepXacklearningreinforcementSim2Real
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2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, and E. Rahm. arXiv preprint arXiv:2409.01329, (September 2024)
3 months ago by @scadsfct
show all tags
ep
FOS:
Machine
sciences
(cs.LG),
Security
Learning
(cs.CV),
and
Vision
Computer
(cs.CR),
Cryptography
information
Pattern
area_bigdata
area_responsibleai
Recognition
epFOS:Machinesciences(cs.LG),SecurityLearning(cs.CV),andVisionComputer(cs.CR),CryptographyinformationPatternarea_bigdataarea_responsibleaiRecognition
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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)
5 months ago by @scadsfct
show all tags
Convolutional
Artificial
intelligence;
Multiple-Instance
deep
neural
networks;
learning
Weakly-supervised
Learning;
transformers;
pathology;
topic_lifescience
Vision
Computational
ConvolutionalArtificialintelligence;Multiple-Instancedeepneuralnetworks;learningWeakly-supervisedLearning;transformers;pathology;topic_lifescienceVisionComputational
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2BioDeepfuse: 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
show all tags
deep
RNA
non-coding
feature
learning
Zno
extraction
BioDeepfuse
classification
deepRNAnon-codingfeaturelearningZnoextractionBioDeepfuseclassification
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2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.
M. Bauer, and C. Augenstein. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, volume 35 of FedCSIS 2023, page 93–101. IEEE, (September 2023)
2 months ago by @scadsfct
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Study
Learning
Computer
Data
Self-Supervised
Unlabelled
Vision.
Comparative
StudyLearningComputerDataSelf-SupervisedUnlabelledVision.Comparative
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2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning
M. Novitasari, J. Quaas, and M. Rodrigues. Environmental Data Science, (2024)
2 months ago by @scadsfct
show all tags
rates
forecasting
machine
autoconversion
learning
satellite
ratesforecastingmachineautoconversionlearningsatellite
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1Common features in lncRNA annotation and classification: A survey
C. Klapproth, R. Sen, P. Stadler, S. Findeiß, and J. Fallmann. Noncoding RNA, 7 (4): 77 (December 2021)
5 months ago by @scadsfct
show all tags
problems;
coding
extraction;
feature
sequence;
machine
lncRNA;
learning
classification
problems;codingextraction;featuresequence;machinelncRNA;learningclassification
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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
show all tags
imported
autoencoder
particle-in-cell
simulation
learning
training
Zno
Continual
importedautoencoderparticle-in-cellsimulationlearningtrainingZnoContinual
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1ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets
K. Schultz, S. Bej, W. Hahn, M. Wolfien, P. Srivastava, and O. Wolkenhauer. Pattern Recognition, (2024)
2 months ago by @scadsfct
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Tabular
Convex
LoRAS
GAN
Imbalanced
data
learning
space
TabularConvexLoRASGANImbalanceddatalearningspace
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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
show all tags
mixed-integer
selection
optimization
meta-learning
machine
learning
Zno
conic
interpretable
cost-sensitive
best
subset
mixed-integerselectionoptimizationmeta-learningmachinelearningZnoconicinterpretablecost-sensitivebestsubset
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1Deep reinforcement learning with artificial microswimmers
R. Pradip, and F. Cichos. Emerging Topics in Artificial Intelligence (ETAI) 2022, 12204, page 104--110. SPIE, (2022)
3 months ago by @scadsfct
show all tags
microswimmers
artificial
learning
topic_physchemistry
reinforcement
Deep
microswimmersartificiallearningtopic_physchemistryreinforcementDeep
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1Enhanced method for reinforcement learning based dynamic obstacle avoidance by assessment of collision risk
F. Hart, and O. Okhrin. Neurocomputing, (2024)
3 months ago by @scadsfct
show all tags
Training
Dynamic
environment
Collision
Reinforcement
learning
metric
risk
avoidance
topic_engineering
obstacle
TrainingDynamicenvironmentCollisionReinforcementlearningmetricriskavoidancetopic_engineeringobstacle
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2Evaluating 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
show all tags
models
Consciousness
Prediction
Syndrome
Predictive
processing
modeling
Theory
algorithms
data
learning
Information
Modeling
Complexity
Processing
Machine
Learning
Training
Neuroscience
Measures
and
Locked-In
Zno
Signal
Computational
modelsConsciousnessPredictionSyndromePredictiveprocessingmodelingTheoryalgorithmsdatalearningInformationModelingComplexityProcessingMachineLearningTrainingNeuroscienceMeasuresandLocked-InZnoSignalComputational
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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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hybrid
machine
patient
{CLIS}
learning
Zno
states
conscious
hybridmachinepatient{CLIS}learningZnostatesconscious
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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
show all tags
descent
axis-aligned
Learning
GradTree
decision
gradient
Zno
trees
descentaxis-alignedLearningGradTreedecisiongradientZnotrees
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1Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection
D. Kiakou, A. Adamopoulos, and N. Scherf. Worldwide Congress on “Genetics, Geriatrics and Neurodegenerative Diseases Research", page 223--230. Springer, (2022)
3 months ago by @scadsfct
show all tags
Neuroimaging
Investigating
Selection
Impact
Disease
Graph-Based
Prediction
topic_neuroinspired
learning
Feature
NeuroimagingInvestigatingSelectionImpactDiseaseGraph-BasedPredictiontopic_neuroinspiredlearningFeature
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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)
5 months ago by @scadsfct
show all tags
neural
networks;
identification;
Recurrent
learning
Haematopoiesis;
unit_transfer
System
Precision
topic_mathfoundation
topic_neuroinspired
Transfer
medicine;
neuralnetworks;identification;RecurrentlearningHaematopoiesis;unit_transferSystemPrecisiontopic_mathfoundationtopic_neuroinspiredTransfermedicine;
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2Insights 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)
2 months ago by @scadsfct
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Mediterranean
Extreme
Learning
Wildfires
Spatiotemporal
Trends
Statistical
Deep
MediterraneanExtremeLearningWildfiresSpatiotemporalTrendsStatisticalDeep
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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
show all tags
Analysis
Learning
Point
Argument
Extractive
Zno
Contrastive
Key
Summarization
AnalysisLearningPointArgumentExtractiveZnoContrastiveKeySummarization
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2Learning 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
show all tags
Learning
neural
algorithms
spiking
Xack
learning
plausible
networks
neurological
LearningneuralalgorithmsspikingXacklearningplausiblenetworksneurological
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publications (hide)41
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1A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving

2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning

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

2BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.

2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning

1Common features in lncRNA annotation and classification: A survey

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

1ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets

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

1Deep reinforcement learning with artificial microswimmers

1Enhanced method for reinforcement learning based dynamic obstacle avoidance by assessment of collision risk

2Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient

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

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

1Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection

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

2Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning

1Key Point Analysis via Contrastive Learning and Extractive Argument Summarization

2Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse

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