Reduce model size to train/test faster.
However, you should actually increase model size to speed up training and inference for transformers
Speeding Up Transformer Training and Inference By Increasing Model Size
https://bair.berkeley.edu/blog/2020/03/05/compress/
paper https://arxiv.org/pdf/2002.11794.pdf
However, you should actually increase model size to speed up training and inference for transformers
Speeding Up Transformer Training and Inference By Increasing Model Size
https://bair.berkeley.edu/blog/2020/03/05/compress/
paper https://arxiv.org/pdf/2002.11794.pdf
The Berkeley Artificial Intelligence Research Blog
Speeding Up Transformer Training and Inference By <i>Increasing</i> Model Size
The BAIR Blog
How a research scientist built Kornia: an open source differentiable library for PyTorch
https://medium.com/pytorch/how-a-research-scientist-built-kornia-an-open-source-differentiable-library-for-pytorch-16e2aa758bc8
https://medium.com/pytorch/how-a-research-scientist-built-kornia-an-open-source-differentiable-library-for-pytorch-16e2aa758bc8
Medium
How a research scientist built Kornia: an open source differentiable library for PyTorch
This is a blog post covering an interview with Edgar Riba, the founding member of Kornia, an open source differentiable CV library.
Diet modulates brain network stability, a biomarker for brain aging, in young adults
https://www.pnas.org/content/early/2020/03/02/1913042117.long
https://www.pnas.org/content/early/2020/03/02/1913042117.long
PNAS
Diet modulates brain network stability, a biomarker for brain aging, in young adults
To better understand how diet influences brain aging, we focus here on the presymptomatic period during which prevention may be most effective. Large-scale life span neuroimaging datasets show functional communication between brain regions destabilizes with…
INTERVIEW WITH JUERGEN SCHMIDHUBER
https://analyticsindiamag.com/lstm-juergen-schmidhuber-artificial-intelligence-switzerland-goedel-machines/
https://analyticsindiamag.com/lstm-juergen-schmidhuber-artificial-intelligence-switzerland-goedel-machines/
Analytics India Magazine
Interview With Juergen Schmidhuber
Juergen Schmidhuber believes that this decade will witness proliferation of Active AI in industrial processes and machines and robots.
Nonlinear neural network dynamics accounts for human confidence in a sequence of perceptual decisions
https://www.biorxiv.org/content/10.1101/648022v3
https://www.biorxiv.org/content/10.1101/648022v3
bioRxiv
NONLINEAR NEURAL NETWORK DYNAMICS ACCOUNTS FOR HUMAN CONFIDENCE IN A SEQUENCE OF PERCEPTUAL DECISIONS
Electrophysiological recordings during perceptual decision tasks in monkeys suggest that the degree of confidence in a decision is based on a simple neural signal produced by the neural decision process. Attractor neural networks provide an appropriate biophysical…
Berkeley's CS294-158 videos is an excellent class on Deep Unsupervised Learning
https://sites.google.com/view/berkeley-cs294-158-sp20/home
https://sites.google.com/view/berkeley-cs294-158-sp20/home
Google
CS294-158-SP20 Deep Unsupervised Learning Spring 2020
About: This course will cover two areas of deep learning in which labeled data is not required: Deep Generative Models and Self-supervised Learning. Recent advances in generative models have made it possible to realistically model high-dimensional raw data…
PRML algorithms implemented in Python
Python codes implementing algorithms described in Bishop's book "Pattern Recognition and Machine Learning" : https://github.com/ctgk/PRML
#DeepLearning #MachineLearning #Python
Python codes implementing algorithms described in Bishop's book "Pattern Recognition and Machine Learning" : https://github.com/ctgk/PRML
#DeepLearning #MachineLearning #Python
GitHub
GitHub - ctgk/PRML: PRML algorithms implemented in Python
PRML algorithms implemented in Python. Contribute to ctgk/PRML development by creating an account on GitHub.
Understanding Self-Training for Gradual Domain Adaptation
Kumar et al.: https://arxiv.org/abs/2002.11361
#ArtificialIntelligence #DeepLearning #MachineLearning
Kumar et al.: https://arxiv.org/abs/2002.11361
#ArtificialIntelligence #DeepLearning #MachineLearning
Artificial intelligence has been used for the first time to instantly and accurately measure blood flow, in a study led by UCL and Barts Health NHS Trust
Image: Myocardial blood flow "perfusion map" created and analysed using AI showing an area of the heart receiving a reduced blood supply (arrow) and putting the patient at risk of heart attacks and other adverse events.
https://www.ucl.ac.uk/news/2020/feb/ai-helps-predict-heart-attacks-and-stroke
Image: Myocardial blood flow "perfusion map" created and analysed using AI showing an area of the heart receiving a reduced blood supply (arrow) and putting the patient at risk of heart attacks and other adverse events.
https://www.ucl.ac.uk/news/2020/feb/ai-helps-predict-heart-attacks-and-stroke
UCL News
AI helps predict heart attacks and stroke
Artificial intelligence has been used for the first time to instantly and accurately measure blood flow, in a study led by UCL and Barts Health NHS Trust.
Severe acute respiratory syndrome coronavirus 2 isolate Wuhan-Hu-1, complete genome
Wu et al.: https://www.ncbi.nlm.nih.gov/nuccore/MN908947.3
Wu et al.: https://www.ncbi.nlm.nih.gov/nuccore/MN908947.3
Carla: Open-source simulator for autonomous driving research
Github:https://github.com/carla-simulator/carla
Paper:http://proceedings.mlr.press/v78/dosovitskiy17a/dosovitskiy17a.pdf
Github:https://github.com/carla-simulator/carla
Paper:http://proceedings.mlr.press/v78/dosovitskiy17a/dosovitskiy17a.pdf
GitHub
GitHub - carla-simulator/carla: Open-source simulator for autonomous driving research.
Open-source simulator for autonomous driving research. - carla-simulator/carla
Blog on "Architecture Comparison of AlexNet, VGGNet, ResNet, Inception, DenseNet" in Towards Data Science.
https://towardsdatascience.com/architecture-comparison-of-alexnet-vggnet-resnet-inception-densenet-beb8b116866d
https://towardsdatascience.com/architecture-comparison-of-alexnet-vggnet-resnet-inception-densenet-beb8b116866d
Medium
Architecture comparison of AlexNet, VGGNet, ResNet, Inception, DenseNet
Layers Denoscription with Hyperparameter and accuracy in ILSVRC Challenge results
Demographic Bias in Biometrics: A Survey on an Emerging Challenge
The main contributions of this article are:
an overview of the topic of algorithmic bias in the context of biometrics,
a comprehensive survey of the existing literature on biometric bias estimation and mitigation,
a discussion of the pertinent technical and social matters, and
an outline of the remaining challenges and future work items, both from technological and social points of view.
https://arxiv.org/pdf/2003.02488.pdf
The main contributions of this article are:
an overview of the topic of algorithmic bias in the context of biometrics,
a comprehensive survey of the existing literature on biometric bias estimation and mitigation,
a discussion of the pertinent technical and social matters, and
an outline of the remaining challenges and future work items, both from technological and social points of view.
https://arxiv.org/pdf/2003.02488.pdf