Regression Planning Networks
Xu et al.: https://arxiv.org/abs/1909.13072
#ArtificialIntelligence #DeepLearning #MachineLearning
Xu et al.: https://arxiv.org/abs/1909.13072
#ArtificialIntelligence #DeepLearning #MachineLearning
arXiv.org
Regression Planning Networks
Recent learning-to-plan methods have shown promising results on planning
directly from observation space. Yet, their ability to plan for long-horizon
tasks is limited by the accuracy of the...
directly from observation space. Yet, their ability to plan for long-horizon
tasks is limited by the accuracy of the...
Python code for Artificial Intelligence - David Poole & Alan Mackworth
Download: https://artint.info/AIPython/aipython.pdf
Download: https://artint.info/AIPython/aipython.pdf
Efficient Graph Generation with Graph Recurrent Attention Networks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #MachineLearning #NeuralNetworks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #MachineLearning #NeuralNetworks
arXiv.org
Efficient Graph Generation with Graph Recurrent Attention Networks
We propose a new family of efficient and expressive deep generative models of graphs, called Graph Recurrent Attention Networks (GRANs). Our model generates graphs one block of nodes and...
Machine learning predicts behavior of biological circuits
https://www.sciencedaily.com/releases/2019/10/191002165235.htm
https://www.sciencedaily.com/releases/2019/10/191002165235.htm
ScienceDaily
Machine learning predicts behavior of biological circuits
Biomedical engineers have devised a machine learning approach to modeling the interactions between complex variables in engineered bacteria that would otherwise be too cumbersome to predict. Their algorithms are generalizable to many kinds of biological systems.
Unsupervised Doodling and Painting with Improved SPIRAL
Mellor et al. : https://arxiv.org/pdf/1910.01007.pdf
Blog : https://learning-to-paint.github.io
#ReinforcementLearning #GenerativeModels #DeepLearning
Mellor et al. : https://arxiv.org/pdf/1910.01007.pdf
Blog : https://learning-to-paint.github.io
#ReinforcementLearning #GenerativeModels #DeepLearning
Identifying Weights and Architectures of Unknown ReLU Networks
David Rolnick and Konrad P. Kording : https://arxiv.org/abs/1910.00744
#DeepLearning #MachineLearning #NeuralNetworks
David Rolnick and Konrad P. Kording : https://arxiv.org/abs/1910.00744
#DeepLearning #MachineLearning #NeuralNetworks
Evolution of learning is key to better artificial intelligence
https://phys.org/news/2019-09-evolution-key-artificial-intelligence.html
https://phys.org/news/2019-09-evolution-key-artificial-intelligence.html
phys.org
Evolution of learning is key to better artificial intelligence
Since "2001: A Space Odyssey," people have wondered: could machines like HAL 9000 eventually exist that can process information with human-like intelligence?
Interpreting Distortions in Dimensionality Reduction by Superimposing Neighbourhood Graphs. https://arxiv.org/abs/1909.12902
arXiv.org
Interpreting Distortions in Dimensionality Reduction by...
To perform visual data exploration, many dimensionality reduction methods
have been developed. These tools allow data analysts to represent
multidimensional data in a 2D or 3D space, while...
have been developed. These tools allow data analysts to represent
multidimensional data in a 2D or 3D space, while...
Learning Neural Causal Models from Unknown Interventions
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio : https://arxiv.org/abs/1910.01075
#MetaLearning #ArtificialIntelligence #CausalModels
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio : https://arxiv.org/abs/1910.01075
#MetaLearning #ArtificialIntelligence #CausalModels
arXiv.org
Learning Neural Causal Models from Unknown Interventions
Promising results have driven a recent surge of interest in continuous optimization methods for Bayesian network structure learning from observational data. However, there are theoretical...
Using computing to fix climate change
Blog by Jack Kelly : https://jack-kelly.com/blog/2019-10-03-using-computing-to-fix-climate-change
#ArtificialIntelligence #ClimateChange #DeepLearning
Blog by Jack Kelly : https://jack-kelly.com/blog/2019-10-03-using-computing-to-fix-climate-change
#ArtificialIntelligence #ClimateChange #DeepLearning
Jack Kelly
Using computing to fix climate change
If you’d like to use computer science to help mitigate climate change, then check out these resources: ClimateChange.AI - All about using AI to mitigate and adapt to climate change. Check out their excellent 2019 paper; sign up to their newsletter, and join…
End-to-End Motion Planning of Quadrotors Using Deep Reinforcement Learning
Efe Camci and Erdal Kayacan : https://arxiv.org/abs/1909.13599
#Robotics #ArtificialIntelligence #ReinforcementLearning
Efe Camci and Erdal Kayacan : https://arxiv.org/abs/1909.13599
#Robotics #ArtificialIntelligence #ReinforcementLearning
"In 2020, we will celebrate that many of the basic ideas behind the Deep Learning Revolution were published three decades ago within fewer than 12 months in our "Annus Mirabilis" 1990-1991:"
@ArtificialIntelligenceArticles
-Jürgen Schmidhuber https://people.idsia.ch/~juergen/deep-learning-miraculous-year-1990-1991.html https://t.iss.one/ArtificialIntelligenceArticles
@ArtificialIntelligenceArticles
-Jürgen Schmidhuber https://people.idsia.ch/~juergen/deep-learning-miraculous-year-1990-1991.html https://t.iss.one/ArtificialIntelligenceArticles
E2E tf.Keras to TFLite to Android
Blog by Margaret Maynard-Reid : https://medium.com/@margaretmz/e2e-tfkeras-tflite-android-273acde6588
#MachineLearning #DeepLearning #TensorFlow #Keras #Android
Blog by Margaret Maynard-Reid : https://medium.com/@margaretmz/e2e-tfkeras-tflite-android-273acde6588
#MachineLearning #DeepLearning #TensorFlow #Keras #Android
Modern problems require modern solutions: Protecting privacy using deepfakes
https://www.profillic.com/paper/arxiv:1909.04538
https://www.profillic.com/paper/arxiv:1909.04538
Profillic
DeepPrivacy: A Generative Adversarial Network for Face Anonymization - Profillic
Explore state-of-the-art in machine learning, AI, and robotics. Browse models, source code, papers by topics and authors. Connect with researchers and engineers working on related problems in machine learning, deep learning, natural language processing, robotics…
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs
https://openreview.net/forum?id=Bkl8YR4YDB
https://openreview.net/forum?id=Bkl8YR4YDB
openreview.net
Large-scale Pretraining for Neural Machine Translation with Tens of...
In this paper, we investigate the problem of training neural machine translation (NMT) systems with a dataset of more than 40 billion bilingual sentence pairs, which is larger than the largest...
The FEYNMAN technique of learning:
Step 1 - Pick and study a topic
Step 2 - Explain the topic to someone, like a child, who is unfamiliar with the topic
Step 3 - Identify any gaps in your understanding
Step 4 - Review and Simplify!
@ArtificialIntelligenceArticles
Step 1 - Pick and study a topic
Step 2 - Explain the topic to someone, like a child, who is unfamiliar with the topic
Step 3 - Identify any gaps in your understanding
Step 4 - Review and Simplify!
@ArtificialIntelligenceArticles
This is Your Brain on Code 🧠💻🔢 computer programming is often associated with math, but researchers used functional MRI scans to show the role of the brain's language processing centers:
https://www.fastcompany.com/3029364/this-is-your-brain-on-code-according-to-functional-mri-imaging
https://www.fastcompany.com/3029364/this-is-your-brain-on-code-according-to-functional-mri-imaging
Fast Company
This Is Your Brain On Code, According To Functional MRI Imaging
Non-coders often associate programming with math, but researchers have used fMRI readings to discover a possible link to the language processing centers of our brains.
TensorFlow 2.0 + Keras overview
For deep learning researchers, by François Chollet : https://colab.research.google.com/drive/1UCJt8EYjlzCs1H1d1X0iDGYJsHKwu-NO
#DeepLearning #MachineLearning #TensorFlow
For deep learning researchers, by François Chollet : https://colab.research.google.com/drive/1UCJt8EYjlzCs1H1d1X0iDGYJsHKwu-NO
#DeepLearning #MachineLearning #TensorFlow
Google
TensorFlow 2.0 + Keras Crash Course.ipynb
Colaboratory notebook
We are releasing a new benchmark and data set to evaluate performance across various neural code search techniques to make it easier to evaluate a new model on a common set of questions. https://ai.facebook.com/blog/neural-code-search-evaluation-dataset/
Facebook
Releasing a new benchmark and dataset for evaluating neural code search models
We are releasing a new benchmark and dataset to evaluate performance across various neural code search techniques to make it easier to evaluate a new model on a common set of questions.