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1Chen-Cai-OSU/awesome-equivariant-network: Paper list for equivariant neural network
https://github.com/Chen-Cai-OSU/awesome-equivariant-network
a year ago by @becker
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1(56) Deep Learning — Andreas Geiger - YouTube
https://www.youtube.com/playlist?list=PL05umP7R6ij3NTWIdtMbfvX7Z-4WEXRqD
a year ago by @becker
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deep
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deeplearninglectureteaching
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1The Predictive Privacy Project - Rainer Mühlhoff
Data Protection in the Context of Big Data and AI
2 years ago by @hotho
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deep
privacy
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machine
Datenschutz
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learning
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ml
deepprivacydatamachineDatenschutzpredictivelearningbigml
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1GitHub - divamgupta/diffusionbee-stable-diffusion-ui: Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed. - GitHub - divamgupta/diffusionbee-stable-diffusion-ui: Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
2 years ago by @hotho
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imagediffusiondeepstablegeneratorlearning
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1NeurIPS 2022 Gaze Meets ML Workshop
https://groups.google.com/g/ml-news/c/F0JgTZQL-Ns/m/H95PMQyTAgAJ?pli=1
2 years ago by @becker
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gaze
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ai
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tracking
eyegazevisualfocusmachineailearningimmermindtracking
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1Healthcare Algorithms Don’t Always Need to Be Generalizable
A Stanford researcher questions the need for generalizable models and proposes instead sharing recipes for creating useful local models.
2 years ago by @becker
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ai
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hospital
generalizationmachineailearningmodelgeneralizehealthhospital
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1https://apic.ai/assets/pdf/apic.aiReportKarlsruhe_20192020.pdf
https://apic.ai/assets/pdf/apic.aiReportKarlsruhe_20192020.pdf
2 years ago by @hotho
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Bilder
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imagebeeBildercvAnzahllearningmodelreport
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1GitHub - grok-ai/nn-template: Generic template to bootstrap your PyTorch project.
https://github.com/grok-ai/nn-template
2 years ago by @becker
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code
cookie
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cutter
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codecookieneuralconfigurationmachinecutterlearningnetworkconfigprogramming
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1The Best GPUs for Deep Learning in 2020 — An In-depth Analysis
https://timdettmers.com/2020/09/07/which-gpu-for-deep-learning/
2 years ago by @becker
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comparison
deep
technical
learning
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benchmark
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1Democratizing access to large-scale language models with OPT-175B
https://ai.facebook.com/blog/democratizing-access-to-large-scale-language-models-with-opt-175b/
2 years ago by @hotho
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LM
deep
Literaturverwaltung
language
learning
model
big
LMdeepLiteraturverwaltunglanguagelearningmodelbig
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1Best GPU for Deep Learning in 2022 (so far)
https://lambdalabs.com/blog/best-gpu-2022-sofar/
2 years ago by @becker
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deep
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nvidia
comparisondeeplearninggpubenchmarknvidia
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1540 Milliarden Parameter: Googles KI-System kann Arithmetik und erkennt Humor | heise online
https://www.heise.de/news/540-Milliarden-Parameter-Googles-KI-System-kann-Arithmetik-und-erkennt-Humor-6664503.html
2 years ago by @hotho
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AI
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KI
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1How to be a machine learning biologist
https://twitter.com/natstann/status/1516428383432941571?t=RGNmFPvykzWjdvYCkoN2oA&s=19
2 years ago by @becker
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youtube
biology
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video
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2GitHub - cornellius-gp/gpytorch: A highly efficient and modular implementation of Gaussian Processes in PyTorch
https://github.com/cornellius-gp/gpytorch
2 years ago by @becker
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bayesian
process
processes
python
inference
pytorch
learning
gpu
gaussian
torch
bayesianprocessprocessespythoninferencepytorchlearninggpugaussiantorch
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1Google AI Blog: KELM: Integrating Knowledge Graphs with Language Model Pre-training Corpora
https://ai.googleblog.com/2021/05/kelm-integrating-knowledge-graphs-with.html
2 years ago by @hotho
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LM
dataset
deep
data
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KG
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LMdatasetdeepdatalearningmodelKGintegration
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1Predicting algorithms - machine learning for index structures
https://www.quantamagazine.org/machine-learning-reimagines-the-building-blocks-of-computing-20220315/
2 years ago by @becker
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subgroup
machine
discovery
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structure
subgroupmachinediscoverylearningindexmlstructure
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1Machine Learning: TensorFlow-Benchmarks auf MacBooks mit M1 Pro und M1 Max | heise online
https://www.heise.de/tests/Machine-Learning-TensorFlow-Benchmarks-auf-MacBooks-mit-M1-Pro-und-M1-Max-6328476.html?seite=all
2 years ago by @hotho
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tensorflow
m1
deep
neural
machine
macbook
learning
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nn
mac
tensorflowm1deepneuralmachinemacbooklearningnetworknnmac
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1microsoft/responsible-ai-toolbox: This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.
https://github.com/microsoft/responsible-ai-toolbox
2 years ago by @becker
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fairness
responsible
machine
ai
toolbox
learning
dashboard
fairnessresponsiblemachineaitoolboxlearningdashboard
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1Deterministic python
https://twitter.com/kastnerkyle/status/1473361479143460872?t=-q6YbOcOZ2AXJ_EgW0vkJg&s=19
2 years ago by @becker
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cuda
random
python
seed
machine
learning
numpy
deterministic
torch
ml
cudarandompythonseedmachinelearningnumpydeterministictorchml
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1Marty Music - YouTube
https://www.youtube.com/channel/UCmnlTWVJysjWPFiZhQ5uudg
3 years ago by @becker
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course
learning
guitar
courselearningguitar
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3Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale
M. Seufert, K. Dietz, N. Wehner, S. Geißler, J. Schüler, M. Wolz, A. Hotho, P. Casas, T. Hoßfeld, and A. Feldmann. IEEE Transactions on Network and Service Management, (2024)
23 days ago by @hotho
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myown
monitoring
machine
2024
learning
network
traffic
myownmonitoringmachine2024learningnetworktraffic
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1Computational Approaches for Connecting Maternal Stress to Preterm Birth
A. Mirzaei, B. Hiller, I. Stelzer, K. Thiele, Y. Tan, and M. Becker. Clinics in Perinatology, (2024)
a month ago by @becker
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myown
stress
pregnancy
machine
learning
computational
myownstresspregnancymachinelearningcomputational
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9Representation Learning: A Review and New Perspectives
Y. Bengio, A. Courville, and P. Vincent. IEEE Trans. Pattern Anal. Mach. Intell., 35 (8): 1798-1828 (2013)
2 months ago by @hotho
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toread
perspectives
review
learning
representation
toreadperspectivesreviewlearningrepresentation
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1Feature-weighted elastic net: using "features of features" for better prediction
J. Tay, N. Aghaeepour, T. Hastie, and R. Tibshirani. Statistica Sinica, 33 (1): 259--279 (January 2023)
3 months ago by @becker
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ien
linear
background
machine
regression
learning
knowledge
bki
ml
informed
integration
ienlinearbackgroundmachineregressionlearningknowledgebkimlinformedintegration
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2Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer
H. Chereda, A. Bleckmann, F. Kramer, A. Leha, and T. Beissbarth. Studies in health technology and informatics, (September 2019)
3 months ago by @becker
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neural
background
gnn
machine
learning
knowledge
networks
graph
bki
ml
informed
integration
neuralbackgroundgnnmachinelearningknowledgenetworksgraphbkimlinformedintegration
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4Optimizing Medical Service Request Processes through Language Modeling and Semantic Search
D. Schlör, J. Pfister, and A. Hotho. 2023 the 7th International Conference on Medical and Health Informatics (ICMHI), page 136–141. New York, NY, USA, Association for Computing Machinery, (2023)
3 months ago by @hotho
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myown
medical
2023
learning
application
representation
llm
myownmedical2023learningapplicationrepresentationllm
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1Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity
N. Ravindra, C. Espinosa, E. Berson, T. Phongpreecha, P. Zhao, M. Becker, A. Chang, S. Shome, I. Marić, D. De Francesco and 1 other author(s). npj Digital Medicine, 6 (1): 171 (2023)
7 months ago by @becker
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sleep
myown
prematurity
deep
activity
accelerometer
pregnancy
learning
representation
sleepmyownprematuritydeepactivityaccelerometerpregnancylearningrepresentation
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1Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature
E. Berson, A. Sreenivas, T. Phongpreecha, A. Perna, F. Grandi, L. Xue, N. Ravindra, N. Payrovnaziri, S. Mataraso, Y. Kim and 9 other author(s). Nature Communications, 14 (1): 4947 (2023)
7 months ago by @becker
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deconvolution
genome
alzheimer
myown
epigenetics
machine
learning
deconvolutiongenomealzheimermyownepigeneticsmachinelearning
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6ConvMOS: climate model output statistics with deep learning
M. Steininger, D. Abel, K. Ziegler, A. Krause, H. Paeth, and A. Hotho. Data Mining and Knowledge Discovery, 37 (1): 136--166 (2023)
7 months ago by @hotho
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MOS
output
myown
deep
2023
learning
climate
ConvMOS
statistics
selected
MOSoutputmyowndeep2023learningclimateConvMOSstatisticsselected
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1Hidden stratification causes clinically meaningful failures in machine learning for medical imaging
L. Oakden-Rayner, J. Dunnmon, G. Carneiro, and C. Ré. Proceedings of the ACM conference on health, inference, and learning, page 151--159. (2020)
11 months ago by @becker
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subgroup
mining
failure
stratification
hidden
machine
pattern
learning
citedby:scholar:count:243
citedby:scholar:timestamp:2023-5-31
subgroupminingfailurestratificationhiddenmachinepatternlearningcitedby:scholar:count:243citedby:scholar:timestamp:2023-5-31
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2Machine learning techniques for accountability
B. Kim, and F. Doshi-Velez. AI Magazine, 42 (1): 47--52 (2021)
a year ago by @becker
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artificial
responsible
machine
ai
citedby:scholar:count:15
learning
intelligence
ml
citedby:scholar:timestamp:2023-4-10
accountability
artificialresponsiblemachineaicitedby:scholar:count:15learningintelligencemlcitedby:scholar:timestamp:2023-4-10accountability
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1Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning
M. Becker, J. Dai, A. Chang, D. Feyaerts, I. Stelzer, M. Zhang, E. Berson, G. Saarunya, D. De Francesco, C. Espinosa and 1 other author(s). Frontiers in Pediatrics, (2022)
a year ago by @becker
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multitask
myown
immune
stress
pregnancy
learning
life
stressors
cell
system
outcomes
machine
adverse
immunology
single
multitaskmyownimmunestresspregnancylearninglifestressorscellsystemoutcomesmachineadverseimmunologysingle
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1Machine Learning Techniques
J. Choi, N. Aghaeepour, and M. Becker. page 147--164. Springer International Publishing, Cham, (2022)
a year ago by @becker
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chapter
myown
book
machine
learning
surgery
chaptermyownbookmachinelearningsurgery
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4Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
P. Villalobos, J. Sevilla, L. Heim, T. Besiroglu, M. Hobbhahn, and A. Ho. arXiv preprint arXiv:2211.04325, (2022)
a year ago by @becker
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set
models
deep
large
sets
data
learning
requirement
datasets
dataset
machine
limit
model
themis
setmodelsdeeplargesetsdatalearningrequirementdatasetsdatasetmachinelimitmodelthemis
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2The Deskilling of Domain Expertise in AI Development
N. Sambasivan, and R. Veeraraghavan. CHI Conference on Human Factors in Computing Systems, page 1--14. (2022)
a year ago by @becker
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domain
artificial
deskilling
machine
citedby:scholar:count:13
ai
learning
knowledge
expertise
themis
intelligence
citedby:scholar:timestamp:2022-12-8
domainartificialdeskillingmachinecitedby:scholar:count:13ailearningknowledgeexpertisethemisintelligencecitedby:scholar:timestamp:2022-12-8
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2Why do tree-based models still outperform deep learning on typical tabular data?
L. Grinsztajn, E. Oyallon, and G. Varoquaux. Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, (2022)
a year ago by @becker
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comparison
forest
decision
neural
data
tabular
learning
tree
trees
network
performance
random
citedby:scholar:count:5
evaluation
citedby:scholar:timestamp:2022-12-1
machine
ml
nn
comparisonforestdecisionneuraldatatabularlearningtreetreesnetworkperformancerandomcitedby:scholar:count:5evaluationcitedby:scholar:timestamp:2022-12-1machinemlnn
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1Interpretable machine learning prediction of all-cause mortality
W. Qiu, H. Chen, A. Dincer, S. Lundberg, M. Kaeberlein, and S. Lee. medRxiv, (2022)
a year ago by @becker
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supervised
distance
citedby:scholar:count:3
machine
collaboration
fuelln
learning
interpretable
citedby:scholar:timestamp:2022-11-30
ml
superviseddistancecitedby:scholar:count:3machinecollaborationfuellnlearninginterpretablecitedby:scholar:timestamp:2022-11-30ml
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3InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images
K. Kobs, M. Steininger, and A. Hotho. (2022)cite arxiv:2211.12760Comment: Accepted to WACV 2023.
a year ago by @hotho
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image
CLIP
myown
deep
language
learning
metric
2022
shot
zero
selected
imageCLIPmyowndeeplanguagelearningmetric2022shotzeroselected
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1Graph representation learning in biomedicine and healthcare
M. Li, K. Huang, and M. Zitnik. Nature Biomedical Engineering, (2022)
a year ago by @becker
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toread
neural
learning
biomedicine
medicine
representation
networks
graph
health
themis
healthcare
toreadneurallearningbiomedicinemedicinerepresentationnetworksgraphhealththemishealthcare
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3Algorithmic fairness datasets: the story so far
A. Fabris, S. Messina, G. Silvello, and G. Susto. Data Mining and Knowledge Discovery, 36 (6): 2074--2152 (Nov 1, 2022)
a year ago by @becker
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fairness
toread
machine
learning
algorithmic
themis
fairnesstoreadmachinelearningalgorithmicthemis
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