On the Relationship between Self-Attention and Convolutional Layers
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi: https://openreview.net/forum?id=HJlnC1rKPB
#ArtificialIntelligence #DeepLearning #Transformers
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi: https://openreview.net/forum?id=HJlnC1rKPB
#ArtificialIntelligence #DeepLearning #Transformers
OpenReview
On the Relationship between Self-Attention and Convolutional Layers
A self-attention layer can perform convolution and often learns to do so in practice.
𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗶𝗻 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲.
Very interesting and comprehensive 67-page article on the applications of AI in health and health care.
Download: https://www.healthit.gov/sites/default/files/jsr-17-task-002_aiforhealthandhealthcare12122017.pdf
Very interesting and comprehensive 67-page article on the applications of AI in health and health care.
Download: https://www.healthit.gov/sites/default/files/jsr-17-task-002_aiforhealthandhealthcare12122017.pdf
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
Hans Pinckaers, Geert Litjens : https://arxiv.org/abs/1910.10470
GitHub : https://github.com/DIAGNijmegen/neural-odes-segmentation
#MedNeurIPS #NeurIPS #NeurIPS2019
arXiv.org
Neural Ordinary Differential Equations for Semantic Segmentation...
Automated medical image segmentation plays a key role in quantitative research and diagnostics. Convolutional neural networks based on the U-Net architecture are the state-of-the-art. A key...
"Linear Algebra"
Instructor : Prof. Gilbert Strang
MIT OpenCourseWare : https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/
#LinearAlgebra #MatrixTheory
Instructor : Prof. Gilbert Strang
MIT OpenCourseWare : https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/video-lectures/
#LinearAlgebra #MatrixTheory
Machine Learning from scratch!
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library, by Quan Tran: https://github.com/anhquan0412/basic_model_scratch
#ArtificialIntelligence #DeepLearning #NeuralNetworks #MachineLearning
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library, by Quan Tran: https://github.com/anhquan0412/basic_model_scratch
#ArtificialIntelligence #DeepLearning #NeuralNetworks #MachineLearning
GitHub
GitHub - anhquan0412/basic_model_scratch: Implementation of some classic Machine Learning model from scratch and benchmarking against…
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library - GitHub - anhquan0412/basic_model_scratch: Implementation of some classic Machine Lea...
Deep RL Bootcamp
By Pieter Abbeel, Rocky Duan, Peter Chen, Andrej Karpathy et al.: https://sites.google.com/view/deep-rl-bootcamp/lectures
#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #ReinforcementLearning
By Pieter Abbeel, Rocky Duan, Peter Chen, Andrej Karpathy et al.: https://sites.google.com/view/deep-rl-bootcamp/lectures
#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #ReinforcementLearning
Blake Richards: Deep Learning with Ensembles of Neocortical Microcircuits
An inspiring talk by Blake Richards at the ICLR2018 emphasizing the interaction between neuroscience and machine learning. This intersection is where great things happen.
http://goo.gl/1YCjrm
https://xn--r1a.website/ArtificialIntelligenceArticles
An inspiring talk by Blake Richards at the ICLR2018 emphasizing the interaction between neuroscience and machine learning. This intersection is where great things happen.
http://goo.gl/1YCjrm
https://xn--r1a.website/ArtificialIntelligenceArticles
YouTube
Blake Richards: Deep Learning with Ensembles of Neocortical Microcircuits (ICLR 2018 invited talks)
Abstract: Deep learning in artificial intelligence (AI) has demonstrated that learning hierarchical representations is a good approach for generating useful sensorimotor behaviors. However, the key to effective hierarchical learning is a mechanism for ""credit…
Artificial Intelligence & #Neuroscience: A Virtuous Circle https://deepmind.com/blog/ai-and-neuroscience-virtuous-circle/
Deepmind
AI and Neuroscience: A virtuous circle
Recent progress in AI has been remarkable. Artificial systems now outperform expert humans at Atari video games, the ancient board game Go, and high-stakes matches of heads-up poker. They can also produce handwriting and speech indistinguishable from those…
Machine Learning Unlocks Library of The Human Brain. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #NeuroScience
http://thetartan.org/2019/11/11/scitech/brain-thoughts
http://thetartan.org/2019/11/11/scitech/brain-thoughts
"Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm"
Chelsea Finn and Sergey Levine : https://arxiv.org/abs/1710.11622
#MachineLearning #ArtificialIntelligence #MetaLearning #NeuralComputing
Chelsea Finn and Sergey Levine : https://arxiv.org/abs/1710.11622
#MachineLearning #ArtificialIntelligence #MetaLearning #NeuralComputing
PyTorch Geometry
The PyTorch Geometry package is a geometric computer vision library for PyTorch
By Arraiy: https://github.com/arraiy/torchgeometry
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PyTorch
The PyTorch Geometry package is a geometric computer vision library for PyTorch
By Arraiy: https://github.com/arraiy/torchgeometry
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PyTorch
GitHub
GitHub - kornia/kornia: Open Source Differentiable Computer Vision Library
Open Source Differentiable Computer Vision Library - GitHub - kornia/kornia: Open Source Differentiable Computer Vision Library
Poly-time universality and limitations of deep learning
Emmanuel Abbe, Colin Sandon : https://arxiv.org/abs/2001.02992
#ArtificialIntelligence #MachineLearning #InformationTheory
Emmanuel Abbe, Colin Sandon : https://arxiv.org/abs/2001.02992
#ArtificialIntelligence #MachineLearning #InformationTheory
State of the art- Photoshop faces with hand sketches!
[https://www.profillic.com/paper/arxiv:2001.02890
(The researchers propose Deep Plastic Surgery, a novel sketch-based image editing framework to achieve both robustness on hand-drawn sketch inputs and the controllability on sketch faithfulness](https://www.profillic.com/paper/arxiv:2001.02890))
[https://www.profillic.com/paper/arxiv:2001.02890
(The researchers propose Deep Plastic Surgery, a novel sketch-based image editing framework to achieve both robustness on hand-drawn sketch inputs and the controllability on sketch faithfulness](https://www.profillic.com/paper/arxiv:2001.02890))
CatalyzeX
Deep Plastic Surgery: Robust and Controllable Image Editing with Human-Drawn Sketches: Model and Code
Click To Get Model/Code. Sketch-based image editing aims to synthesize and modify photos based on the structural information provided by the human-drawn sketches. Since sketches are difficult to collect, previous methods mainly use edge maps instead of sketches…
Immediate brain plasticity after one hour of brain–computer interface (BCI)
https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP278118
https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP278118
The Physiological Society
Immediate brain plasticity after one hour of brain–computer interface (BCI)
Two groups of inexperienced brain-computer interface users underwent a purely mental EEG-BCI session that rapidly impacted on their brain.
Modulations in structural and functional MRI were found aft...
Modulations in structural and functional MRI were found aft...
THE AMALGAMATION OF DATA SCIENCE AND NEUROSCIENCE
https://www.analyticsinsight.net/the-amalgamation-of-data-science-and-neuroscience/
https://www.analyticsinsight.net/the-amalgamation-of-data-science-and-neuroscience/
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data. http://arxiv.org/abs/2001.02799
Lifted Hybrid Variational Inference. http://arxiv.org/abs/2001.02773
Named-Entity-Recognition-NER-Papers
By Pengfei Liu, Jinlan Fu and other contributors: https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
An elaborate and exhaustive paper list for Named Entity Recognition (NER), covering papers from seven top conferences (ACL / EMNLP / NAACL / Coling / ICLR / AAAI / IJCAI) and eight years (2013-2020).
#ArtificialIntelligence #DeepLearning #MachineLearning
By Pengfei Liu, Jinlan Fu and other contributors: https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
An elaborate and exhaustive paper list for Named Entity Recognition (NER), covering papers from seven top conferences (ACL / EMNLP / NAACL / Coling / ICLR / AAAI / IJCAI) and eight years (2013-2020).
#ArtificialIntelligence #DeepLearning #MachineLearning
GitHub
GitHub - pfliu-nlp/Named-Entity-Recognition-NER-Papers: An elaborate and exhaustive paper list for Named Entity Recognition (NER)
An elaborate and exhaustive paper list for Named Entity Recognition (NER) - pfliu-nlp/Named-Entity-Recognition-NER-Papers
Summary: A new convolutional neural network that utilizes MRI brain scans can forecast genetic mutations in glioma brain tumors.
Source: Osaka University
Researchers at Osaka University have developed a computer method that uses magnetic resonance imaging (MRI) and machine learning to rapidly forecast genetic mutations in glioma tumors, which occur in the brain or spine. The work may help glioma patients to receive more suitable treatment faster, giving better outcomes. The research was recently published in Scientific Reports.
https://neurosciencenews.com/genetics-brain-tumors-15451/
Source: Osaka University
Researchers at Osaka University have developed a computer method that uses magnetic resonance imaging (MRI) and machine learning to rapidly forecast genetic mutations in glioma tumors, which occur in the brain or spine. The work may help glioma patients to receive more suitable treatment faster, giving better outcomes. The research was recently published in Scientific Reports.
https://neurosciencenews.com/genetics-brain-tumors-15451/
Detection of anaemia from retinal fundus images via deep learning https://www.nature.com/articles/s41551-019-0487-z.epdf?shared_access_token=BcBD1jh7EFkbhRR7GO7epNRgN0jAjWel9jnR3ZoTv0PM60VmCAPkIZuQsecTYZaovpLrjs4HpzIZT_r4kkYc5fNlZWatHh0N1icwpncYARKL54pqNmeNIjwcQ2eQ63-__htO1uHXwZ7GinlLrmJhhQ%3D%3D