Top 10 #deeplearning research papers as per this website
https://lnkd.in/dPYayt9

Of course the choice remains biased but we do like these besides a few hundred other papers.

Remember, it is not the popular but the meaningful and industry relevant research that is worth paying attention to.

Here's the list:

1. Universal Language Model Fine-tuning for Text Classification
https://lnkd.in/dhj5SyM

2. Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
https://lnkd.in/d44kt3Q

3. Deep Contextualized Word Representations
https://lnkd.in/dkP68Fb

4. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
https://lnkd.in/dAhYzge

5. Delayed Impact of Fair Machine Learning
https://lnkd.in/dvTvG2s

6. World Models

7. Taskonomy: Disentangling Task Transfer Learning
https://lnkd.in/dYxMjAd

8. Know What You Don’t Know: Unanswerable Questions for SQuAD
https://lnkd.in/d--grME

9. Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://lnkd.in/dY6psf4

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://lnkd.in/dgtnD7n
#machinelearning #research #deeplearning #artificialintelligence

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

The Evolved Transformer

Paper by So et al.: https://lnkd.in/eNZ6ije

#artificalintelligence #MachineLearning #NeuralComputing #EvolutionaryComputing #research

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Our friends in Tampere University are hiring now:
15 fully-funded PhD job openings for 3 years within H2020 A-WEAR European Joint Doctorate

Target audience: fresh MSc graduates in various engineering fields (who have completed their first master no earlier than Fall 2015) and who are passionate about pursuing a PhD in a research field of high relevance to today’s society (wearable computing & IoT).


Job description: fully funded 36 months PhD positions towards double/joint PhD programs in 5 top European technical universities in Finland, Italy, Spain, Czech Republic, and Romania

Gross salary (approx. in EUR/month): 3600 (FI), 2800 (ES), 2000 (RO), 2400 (CZ), 2900 (IT)

Application deadline: 28th of February 2019

Starting time of the PhD: Fall 2019
https://www.tuni.fi/en
https://lnkd.in/eyDattx

#universities #graduations #phd #funding #research

✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv

TensorFlow 2.0 is the best bet for Deep Learning Community.

Eager execution for easy prototyping & debugging along with tf.function() advantage,

Distribution Strategies for distributed Training (including multi node, multi accelerator including TPU pods, also Kubernetes),

Smoother building, training,validation with tf.keras and premade Estimators,

Smart deployment (TensorFlow Serving(A TensorFlow library allowing models to be served over HTTP/REST), TensorFlow Lite(TensorFlow’s lightweight solution for mobile and embedded devices), TensorFlow.js(Enables deploying models in JavaScript environments, such as in a web browser or server side through Node.js), TensorFlow Hub),
Compatiable with TF 1.x (also a conversion tool which updates TensorFlow 1.x Python code to use TensorFlow 2.0 compatible APIs, or flags cases where code cannot be converted automatically )

Also great for researchers ( Model Subclassing API, automatic differentiation, Ragged Tensors, TensorFlow Probability, Tensor2Tensor)

For beginners, TensorFlow, https://lnkd.in/fp3AWKk

#tensorflow #research #deeplearning #pyTorch

✴️ @AI_Python_EN

OpenAI has created activation atlases (in collaboration with Google researchers), a new technique for visualizing what interactions between neurons can represent.

As AI systems are deployed in increasingly sensitive contexts, having a better understanding of their internal decision-making processes will let us identify weaknesses and investigate failures.

Blog: https://lnkd.in/d4i6xQC
Paper: https://lnkd.in/dGNcd4K
Github: https://lnkd.in/d-2WhfN
Demo: https://lnkd.in/dBiHZv3

#deeplearning #research

✴️ @AI_Python_EN

Do you remember a bullshit study published a few years ago claiming that deep learning can spot criminals from their photos and arguing that criminals have different facial features. Despite the ethical issue, we know this is bullshit but we couldn't spot the flaws.
Well, like most machine learning problems the devil is in the data.
To train the model the researchers used 700 of criminals ID photos as positive images. On other hands, they collected 1100 non-criminals from the web which featured people smiling.
No wonder why they go 90% accuracy!
So instead of developing criminals detector, they developed smiles detector LOL.
#research #machinelearning #deeplearning #ai
https://lnkd.in/fMhU4ZZ

✴️ @AI_Python_EN

Hacking Google reCAPTCHA v3 using Reinforcement Learning

Paper: https://lnkd.in/es9AjzC

#reinforcementlearning #research #ai #artificialintelligence #machinelearning

✴️ @AI_Python_EN

Towards Structured Evaluation of Deep Neural Network Supervisors

Paper: https://lnkd.in/evfuQAq

#neuralnetworks #ai #machinelearning #artificialintelligence #deeplearning #research

✴️ @AI_Python_EN

neuralRank: Searching and ranking ANN-based model repositories

Paper: https://lnkd.in/edxKPBH
#artificialinteligence #research #machineleaning #neuralnetworks

✴️ @AI_Python_EN

OpenAI has created activation atlases (in collaboration with Google researchers), a new technique for visualizing what interactions between neurons can represent.

As AI systems are deployed in increasingly sensitive contexts, having a better understanding of their internal decision-making processes will let us identify weaknesses and investigate failures.

Blog: https://lnkd.in/d4i6xQC
Paper: https://lnkd.in/dGNcd4K
Github: https://lnkd.in/d-2WhfN
Demo: https://lnkd.in/dBiHZv3

#deeplearning #research

✴️ @AI_Python_EN

#Datascience needs to move beyond #research to actually make a real impact in the #AI economy.

Agree?

#DeepLearning #artificialintelligence #machinelearning

✴️ @AI_Python_EN

#DeepLearning is fun when you have loads of GPUs!

Here's a 256GB , 8 GPU cluster we will soon be testing as well.

#gpu #nvidia #research
#machinelearning
✴️ @AI_Python_EN

Machine Learning (ML) & Artificial Intelligence (AI): From Black Box to White Box Models in 4 Steps - Resources for Explainable AI & ML Model Interpretability.

✔️STEP 1 - ARTICLES

- (short) KDnuggets article: https://lnkd.in/eRyTXcQ

- (long) O'Reilly article: https://lnkd.in/ehMHYsr

✔️STEP 2 - BOOKS

- Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (free e-book): https://lnkd.in/eUWfa5y

- An Introduction to Machine Learning Interpretability: An Applied Perspective on Fairness, Accountability, Transparency, and Explainable AI (free e-book): https://lnkd.in/dJm595N

✔️STEP 3 - COLLABORATE

- Join Explainable AI (XAI) Group: https://lnkd.in/dQjmhZQ

✔️STEP 4 - PRACTICE

- Hands-On Practice: Open-Source Tools & Tutorials for ML Interpretability (Python/R): https://lnkd.in/d5bXgV7

- Python Jupyter Notebooks: https://lnkd.in/dETegUH

#machinelearning #datascience #analytics #bigdata #statistics #artificialintelligence #ai #datamining #deeplearning #neuralnetworks #interpretability #science #research #technology #business #healthcare

✴️ @AI_Python_EN

Today, #LIDAR is used in all autonomous cars except in Tesla

Lidar sensors are big, bulky, expensive, and ugly to look at. Not only that, they do a poor job in snow, sleet, hail, smoke, and smog. If you can’t see the road ahead, neither can LIDAR!.

That last part is one of the reasons Elon Musk refuses to incorporate lidar sensors into the self-driving hardware package for Tesla cars.

Apple & Cornell University have solved the problem of depth precision and this paves the way for faster adoption for safer yet cheaper cars!

Read more here: https://lnkd.in/dZgS6id
Research paper: https://lnkd.in/djRhzq3
#research #selfdriving #deeplearning

✴️ @AI_Python_EN

What type of a presenter are you?

Are you a "diva", a "penguin" or "Mr. Toscanini"?

Presenting your #MachineLearning #AI #research or project is an art which you must master very well to succeed.

In our internal lectures / classes we do our best to teach our team members to develop a great storyline and present like a star.

#presentationskills #AI #soft #skills

✴️ @AI_Python_EN

"Training Neural Nets on Larger Batches: Practical Tips for 1-GPU, Multi-GPU & Distributed setups"

By Thomas Wolf: https://lnkd.in/etyMzjQ

#ArtificialInteligence #DeepLearning #MachineLearning #NeuralNetworks #Research

✴️ @AI_Python_EN

RetinaFace: Single-stage Dense Face Localisation in the Wild.

Though tremendous strides have been made in uncontrolled face detection, accurate and efficient face localisation in the wild remains an open challenge.

This paper presents a robust single-stage face detector, named RetinaFace, which performs pixel-wise face localisation on various scales of faces by taking advantages of joint extra-supervised and self-supervised multi-task learning.


Paper: https://lnkd.in/dF48muv
#deeplearning #facerecognition #research

✴️ @AI_Python_EN

Fundamentals of Clinical Data Science (Open-Access Book) - for healthcare & IT professionals: https://lnkd.in/eacNnjz
#
For more interesting & helpful content on healthcare & data science, follow me and Brainformatika on LinkedIn.

Table of Contents

Part I. Data Collection

- Data Sources
- Data at Scale
- Standards in Healthcare Data
- Research Data Stewardship for Healthcare Professionals
- The EU’s General Data Protection Regulation (GDPR) in a Research Context

Part II. From Data to Model

- Preparing Data for Predictive Modelling
- Extracting Features from Time Series
- Prediction Modeling Methodology
- Diving Deeper into Models
- Reporting Standards & Critical Appraisal of Prediction Models

Part III. From Model to Application

- Clinical Decision Support Systems
- Mobile Apps
- Optimizing Care Processes with Operational Excellence & Process Mining
- Value-Based Health Care Supported by Data Science

#healthcare #datascience #digitalhealth #analytics #machinelearning #bigdata #populationhealth #ai #medicine #informatics #artificialintelligence #research #precisionmedicine #publichealth #science #health #innovation #technology #informationtechnology

✴️ @AI_Python_EN

The Best and Most Current of Modern Natural Language Processing

Blog by Victor Sanh: https://lnkd.in/emch8gG

#NaturalLanguageProcessing #MachineLearning #NLP #DeepLearning #Research

✴️ @AI_Python_EN

Have you heard of "R-Transformer?", a Recurrent Neural Network Enhanced Transformer

Recurrent Neural Networks have long been the dominating choice for sequence modeling. However, it severely suffers from two issues: impotent in capturing very long-term dependencies and unable to parallelize the sequential computation procedure.

Therefore, many non-recurrent sequence models that are built on convolution and attention operations have been proposed recently.

Here the authors propose the R-Transformer which enjoys the advantages of both RNNs and the multi-head attention mechanism while avoids their respective drawbacks.

The proposed model can effectively capture both local structures and global long-term dependencies in sequences without any use of position embeddings. They evaluated R-Transformer through extensive experiments with data from a wide range of domains and the empirical results show that R-Transformer outperforms the state-of-the-art methods by a large margin in most of the tasks.

Github code: https://lnkd.in/dpFckix

#research #algorithms #machinelearning #deeplearning #rnn

✴️ @AI_Python_EN