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The science of deep learning
2020
Proceedings of the National Academy of Sciences of the United States of America
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artificial intelligence | machine learning | deep learning | neural networks www.pnas.org/cgi/ ...
Acknowledgments The authors thank Dame Jillian Sackler for her many years of sponsorship of National Academy of Sciences Sackler Colloquia. ...
Many graduate students came to Washington, DC from around the United States to participate actively. The National Academy of Sciences and PNAS staff have also been very helpful at every stage. ...
doi:10.1073/pnas.2020596117
pmid:33229565
fatcat:hf4io3euobaungvigwvp2nzkpq
Reproducible Science of Deep Learning: The Pruning Case Study
[article]
2020
figshare.com
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facilitated the investigation of the behavior of pruned models. ...
I will highlight examples such as the contribution of centralized, reusable pruning methods in PyTorch and the open-sourcing of the 'dagger' framework for reproducible and reusable experiment orchestration ...
Measurements are affected by
sources of variations
What can we learn from the
other sciences?
2. ...
doi:10.6084/m9.figshare.12991199.v1
fatcat:jcdl6v64czezdaem4ujaizwmgu
The Role of Citizen Science and Deep Learning in Camera Trapping
2021
Sustainability
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Our approach aims to show a new perspective and to update the recent progress in engaging the enthusiasm of citizen scientists and in including machine learning processes into image classification in camera ...
This approach (combining machine learning and the input from citizen scientists) may significantly assist in streamlining the processing of camera trap data while simultaneously raising public environmental ...
Our thanks also go to Steve Ridgill and the second native speaker for the English improvements of the text.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/su131810287
fatcat:xa7nvzd47vbhjc4wgtysv4azui
Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science
2020
Journal of Mathematical Imaging and Vision
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Many mathematically inclined researchers have a strong desire to understand the theoretical reasons for the success of these approaches and to find relations between deep learning and mathematically well-established ...
Deep learning methods have become an omnipresent and highly successful part of recent approaches in imaging and vision. ...
deep learning. ...
doi:10.1007/s10851-020-00955-8
fatcat:n5kayejz4fcxxk5dvfit3gsbru
Deep Learning by Doing: The NVIDIA Deep Learning Institute and University Ambassador Program
2019
The Journal of Computational Science Education
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, and engineers solve real-world problems in a wide range of domains using deep learning and accelerated computing. ...
Advanced and domain-specific courses in deep learning are also available. ...
ACKNOWLEDGMENTS The authors would like to thank NVIDIA Deep Learning Institute for providing the figures, documents and online course platform, and Tokyo Institute of Technology and ACM University of Kentucky ...
doi:10.22369/issn.2153-4136/10/1/16
fatcat:zb5mfkg2aza6dar6gdzj2zfqxq
Deep Learning for Deep Waters: An Expert-in-the-Loop Machine Learning Framework for Marine Sciences
2021
Journal of Marine Science and Engineering
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Driven by the unprecedented availability of data, machine learning has become a pervasive and transformative technology across industry and science. ...
Its advantages are demonstrated with our novel deep learning-based expert-in-the-loop framework for automatic detection of turbulent wake signatures in echo sounder data. ...
The framework also serves as a demonstration of general applicability of the deep learning approach in marine sciences. ...
doi:10.3390/jmse9020169
fatcat:3y2oviaj7nckdfy5stmybqasti
Deep Loving - The Friend of Deep Learning
2020
Global Journal of Computer Science and Technology
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The definition of Deep Learning is shown followed by a literature review of the "Deep Loving" field. ...
In this article, we coin the term "Deep Loving". After the publication of this article, "Deep Loving" will be considered as the friend of Deep Learning. ...
Acknowledgments Thanks to Very Excellent Editorial Team of "Global Journal of Computer Science and Technology (GJCST)" and reviewers for accepting our innovative invention titled "Deep Loving." ...
doi:10.34257/gjcstdvol20is1pg51
fatcat:bwx77ssllvhajn7aegy5i3c4ve
Deep learning in deep time
2020
Proceedings of the National Academy of Sciences of the United States of America
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The crux of the authors' approach is the combination of recently developed high-resolution microscope technology (11) with deep convolutional neural networks (CNNs), powerful machine-learning models developed ...
Romero et al. (9) show how this record can be further refined with deep learning. ...
science of deep learning. ...
doi:10.1073/pnas.2020870117
pmid:33168754
fatcat:3eff66s32fedtm3d5av5jkm62u
Are There Deep Reasons Underlying the Pathologies of Today's Deep Learning Algorithms?
[chapter]
2015
Lecture Notes in Computer Science
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It is hypothesized that these behaviors are tied with limitations in the internal representations learned by these architectures, and that these same limitations would inhibit integration of these architectures ...
Some currently popular and successful deep learning architectures display certain pathological behaviors (e.g. confidently classifying random data as belonging to a familiar category of nonrandom images ...
Broad and Narrow Interpretations of "Deep Learning" In his book"Deep Learning" [11] , cognitive scientist Stellan Ohlson formulates the concept of deep learning as a general set of information-processing ...
doi:10.1007/978-3-319-21365-1_8
fatcat:drynikjyujeetpdsgaa3xyxuym
Machine Learning and Deep Learning: Introduction and Applications
2020
Journal of the Society of Materials Science Japan
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Furthermore, deep neural networks are explained as the extention to the three-layered neural networks. Finally, the application of the deep neural networks are shown with some examples. ...
Most of the time, they refer machine learning when AI is discussed. This paper gives introduction to machine learning. First, the overview of the machine learning is given. ...
· ⃗ x + w0} (4) (2) (4) 1 + exp{− ∑ i ⃗ w · ⃗ x + w0} | (5) 2 2 E E = 1 2 e 2 = 1 2 (y − yt) 2 (6) E E ⃗ w, w0 E (6) E 5 E w E w* 傾きが負のとき 傾きが正のとき ↗ w を増加させる ↘ w を減少させる E Fig. 5 Graphical illustration of ...
doi:10.2472/jsms.69.633
fatcat:mwos4cedsrfbvc3usnsuldrsmi
A REVIEW ON THE CONCEPT OF DEEP LEARNING
2020
International Journal of Innovative Research in Computer Science & Technology
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ANN is used by many online stores in the form of recommendation systems to offer suitable products based on their liking. ...
In this work based on artificial neural network recurrent and convolutional network is proposed at the level of letters in order to classify and sort textual information with given classes. ...
It was proposed for effective image recognition [1] by Yann LeCun and is a type of deep learning algorithm. ...
doi:10.21276/ijircst.2020.8.3.16
fatcat:xp6et5ukifgmbgvhq2nhsdsouu
The Design of Learning Activity in Flipped Classroom Based on Deep Learning Theory
2017
DEStech Transactions on Social Science Education and Human Science
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of deep learning and surface learning. ...
This paper puts forward the idea of transformation to the teaching design paradigm of the flipped classroom, designs the model of learning activity in flipped classroom based on deep learning theory. ...
The purpose of deep learning is to practice, which is to solve the problem as the deep inquiry learning for the kernel, so it is the process of application and innovation of acquisition knowledge. ...
doi:10.12783/dtssehs/hsmet2017/16459
fatcat:t6wxgvdmlzdldprp5hy74l4jy4
Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory
2020
Applied Sciences
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The results suggest that every person produces a unique trajectory of underfoot pressures while walking and that CNNs can learn the distinctive features of these trajectories. ...
The best CNN classified a separate set containing 2,250 segments with an overall accuracy of 99.9%. A second set of 4,500 segments from the six remaining subjects was then used for transfer learning. ...
Acknowledgments: The author gratefully thanks his daughter Laureline for proofreading the manuscript.
Conflicts of Interest: The author declares no conflict of interest. ...
doi:10.3390/app10030774
fatcat:iumbfk22drawzfh65eaozfzbxy
The Experience of Deep Learning by Accounting Students
2011
Social Science Research Network
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An implication of this study is the need to support accounting students to experience deep learning in first year courses to enable them to develop personal capabilities in their later university studies ...
To do this, they need to experience deep learning. This study examines how to support accounting students to experience deep learning. ...
Acknowledgements: We would like to acknowledge the valuable input and contribution of Professor Tom Angelo, La Trobe University. ...
doi:10.2139/ssrn.1912131
fatcat:kz56te2yxrcp7ikk2mojyp4lkm
Interactions Between Students and Tutor in Problem-Based Learning: The Significance of Deep Learning
2009
Kaohsiung Journal of Medical Sciences
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ACKNOWLEDGMENTS The author would like to thank the President of the Kaohsiung Medical University, Professor Hsin-Su Yu, the Dean of the College of Medicine, Professor Chung-Sheng Lai, and Associate Dean ...
, Professor Keh-Min Liu, for inviting him as a keynote speaker on this topic in the International Conference on Problem-Based Learning, which was held in Kaohsiung, Taiwan, in July 2008. ...
The problems in the group are related to superficial learning (absence of deep learning). ...
doi:10.1016/s1607-551x(09)70068-3
pmid:19502144
fatcat:ibilfkpiafdkhaokxt3ffbzeom
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