U-GAT-IT

Official TensorFlow Implementation : https://github.com/taki0112/UGATIT

#DeepLearning #Tensorflow #UnsupervisedLearning

Postdoc position in Machine Learning @ German Aerospace Center (DLR)

The German Aerospace Center's Institute of Data Science in Jena, Germany, is currently seeking a postdoc with at least 3 years' experience in deep learning.

Our newly established machine learning group focuses on developing deep learning approaches for a broad range of applications. This group maintains a close cooperation with the Remote Sensing Technology Institute in Oberpfaffenhofen, and is in frequent contact with other institutes of the German Aerospace Center (DLR). As such, the developed methods will be applied and evaluated in various domains with close relevance to applications within DLR, particularly earth observation. Quality control for these methods is also emphasized; aspects of this include validation, robustness, uncertainty modeling, and interpretability. This position will focus in particular on the development of novel approaches for low-resource tasks and noisy data.

A full description of the position, including the link to the application portal, is available here:
https://www.dlr.de/dlr/jobs/en/desktopdefault.aspx/tabid-10596/1003_read-33291/

For questions, please do not hesitate to contact me.

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Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Institute of Data Science | Data Management and Analysis | Mälzerstraße 3 | D-07745 Jena
Dr. Anna Kruspe | Acting Group Lead Machine Learning
Telefon +49 3641 30960 127 | [email protected]
DLR.de

Predicting Prosodic Prominence from Text with Pre-trained Contextualized Word Representations

Talman et al.: https://arxiv.org/abs/1908.02262

GitHub: https://github.com/Helsinki-NLP/prosody

#dataset #machinelearning #naturallanguageprocessing

Example of how deep fake can save the world)
https://www.youtube.com/watch?v=Y1HGgICqZ3c

At the heart of most deep learning generalization bounds (VC, Rademacher, PAC-Bayes) is uniform convergence (u.c.). We argue why u. c. may be unable to provide a complete explanation of generalization, even if we take into account the implicit bias of SGD.

https://arxiv.org/pdf/1902.04742.pdf

https://t.iss.one/ArtificialIntelligenceArticles

Deep-learning algorithms can be applied to large datasets of electrocardiograms, are capable of identifying abnormal heart rhythms and mechanical dysfunction, and could aid healthcare decisions: (link: https://go.nature.com/2HFYd2o) go.nature.com/2HFYd2o

ice work on how to sync different videos
https://ai.googleblog.com/2019/08/video-understanding-using-temporal.html

Few things are closer to my heart than Graphs and Machine Learning. This survey paper looks at deep learning techniques for handling graphs:

https://arxiv.org/pdf/1812.04202.pdf

Stanford computer scientists developed a deep learning algorithm that can diagnose heart rhythm defects better than cardiologists.

https://stanford.io/2BnLYzB

Excellent post on achieving state-of-the-art heart disease diagnosis using deep learning (dilated U-Net in Keras): https://blog.insightdatascience.com/heart-disease-diagnosis-with-deep-learning-c2d92c27e730 https://t.iss.one/ArtificialIntelligenceArticles

Know here everything about Julia - the programming language making Machine Learning (ML) better. 💻

https://appinventiv.com/blog/introducing-julia-machine-learning-development-language/

DoorGym: A Scalable Door Opening Environment and Baseline Agent
Urakami et al.: https://arxiv.org/pdf/1908.01887v1.pdf
#DeepLearning #ReinforcementLearning #Robotics

Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron Courville, Marc G. Bellemare : https://arxiv.org/abs/1908.02388
#deeplearning #machinelearning #reinforcementlearning

Machine Learning Yearning (Draft Version)
By Andrew Ng: https://d2wvfoqc9gyqzf.cloudfront.net/content/uploads/2018/09/Ng-MLY01-13.pdf
#100DaysOfMLCode #ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks

"Linear Algebra"

Instructor : Prof. Gilbert Strang

MIT OpenCourseWare : https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/

#LinearAlgebra #MatrixTheory

Compressing BERT for faster prediction
Blog by Sam Sucik : https://blog.rasa.com/compressing-bert-for-faster-prediction-2/
#ArtificialIntelligence #NaturalLanguageProcessing #UnsupervisedLearning

https://www.theverge.com/platform/amp/2018/9/5/17822562/google-dataset-search-service-scholar-scientific-journal-open-data-access

#youtube.com/c/MirrorNeuron

New Releases: PyTorch 1.2, torchtext 0.4, torchaudio 0.3, and torchvision 0.4
Blog by Team PyTorch : https://pytorch.org/blog/pytorch-1.2-and-domain-api-release/
GitHub : https://github.com/pytorch/pytorch/releases/tag/v1.2.0
#deeplearning #machinelearning #pytorch

From TensorFlow to PyTorch
By Thomas Wolf : https://medium.com/huggingface/from-tensorflow-to-pytorch-265f40ef2a28
#deeplearning #pytorch #tensorflow

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation

https://arxiv.org/abs/1908.00061v1