A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey
[article]
2019
arXiv
pre-print
Preserved Fulltext
In this survey we differ the mechanisms and properties of explaining systems for Deep Neural Networks for Computer Vision tasks. ...
As a black box model due to their multilayer nonlinear structure, Deep Neural Networks are often criticized to be non-transparent and their predictions not traceable by humans. ...
Most used DNNs for image or video processing [39] , [40] , [41] are Convolutional Neural Networks (CNNs) [42] , for videos [41] or sequences of text Recurrent Neural Networks (RNNs) [43] , and ...
arXiv:1911.12116v1
fatcat:qgeg6rz6qzgrfikhsgah77yz2a
Deep Learning of Representations: Looking Forward
[article]
2013
arXiv
pre-print
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
Other Versions
Deep learning research aims at discovering learning algorithms that discover multiple levels of distributed representations, with higher levels representing more abstract concepts. ...
to much larger models and datasets, reducing optimization difficulties due to ill-conditioning or local minima, designing more efficient and powerful inference and sampling procedures, and learning to disentangle ...
He is also grateful for the funding support from NSERC, CIFAR, the Canada Research Chairs, and Compute Canada. ...
arXiv:1305.0445v2
fatcat:cyfgf5trljfopcjsapicf4ay3q
Enforcing and Discovering Structure in Machine Learning
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Stopping criterion We propose a stopping criterion for boosting VI, which allows us to identify when a reasonably good approximation is reached and save computational effort. ...
This indicates that the specific representation used matters and that predictions with lower unfairness can be achieved. ...
The best weakly-supervised disentanglement methods thus learn representations that are useful for training accurate classifiers downstream. ...
arXiv:2111.13693v1
fatcat:2urmfjeh6nhvjeiv3qoiy5hrum
RGB-D-based Human Motion Recognition with Deep Learning: A Survey
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Specifically, deep learning methods based on the CNN and RNN architectures have been adopted for motion recognition using RGB-D data. ...
Particularly, we highlighted the methods of encoding spatial-temporal-structural information inherent in video sequence, and discuss potential directions for future research. ...
[131] proposed a Disentangled Representation learning Generative Adversarial Networks (DR-GAN) for pose-invariant face recognition. ...
arXiv:1711.08362v2
fatcat:cugugpqeffcshnwwto4z2aw4ti
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
causal inference; (5) Complete supervised disentanglement of neural networks; (6) Complete or even partial unsupervised disentanglement of neural networks; (7) Dimensionality reduction for data visualization ...
Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting. ...
Acknowledgments We thank Leonardo Lucio Custode for pointing out several useful references to Challenge 10. Thank you to David Page for providing useful references on early explainable ML. ...
arXiv:2103.11251v2
fatcat:52llnswt3ze5rl3zhbai5bscce
Facial Keypoint Sequence Generation from Audio
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This dataset is then further used to train the model, Audio2Keypoint, a novel approach for synthesizing facial keypoint movement to go with the audio. ...
To address this, a unique audio-keypoint dataset of over 150,000 videos at 224p and 25fps is introduced that relates the facial keypoint movement for the given audio. ...
Later, these can be used for the generation of photo-realistic videos. ...
arXiv:2011.01114v1
fatcat:ru3q4xmqgrgoph3tcqlgah26bq
VirtualCube: An Immersive 3D Video Communication System
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2112.06730v1 fatcat:gdnrqgmh7bcz3dd3hsb7ehe2cm
The key ingredient is VirtualCube, an abstract representation of a real-world cubicle instrumented with RGBD cameras for capturing the 3D geometry and texture of a user. ...
To achieve real-time rendering of remote participants, we develop the V-Cube View algorithm, which uses multi-view stereo for more accurate depth estimation and Lumi-Net rendering for better rendering ...
adversarially disentangled audio-visual representation. In AAAI, vol. 33,
Kang, P. Kohli, Y. Lutchyn, C. Keskin, and S. Izadi. ...
arXiv:2112.06730v2
fatcat:ce7dls4fvbf7zbyqdn7mx4hvpe
Towards Causal Representation Learning
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
A central problem for AI and causality is, thus, causal representation learning, the discovery of high-level causal variables from low-level observations. ...
Finally, we delineate some implications of causality for machine learning and propose key research areas at the intersection of both communities. ...
Thanks to Wouter van Amsterdam for pointing out typos in the first version. We also thank Thomas Kipf, Klaus Greff, and Alexander d'Amour for the useful discussions. ...
arXiv:2102.11107v1
fatcat:n25xwac72nfulgl3gvvs4kerca
Toward Causal Representation Learning
2021
Proceedings of the IEEE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
A central problem for AI and causality is, thus, causal representation learning, that is, the discovery of highlevel causal variables from low-level observations. ...
Finally, we delineate some implications of causality for machine learning and propose key research areas at the intersection of both communities. ...
It has recently been used for learning causal models [131] , modular architectures [29] , [85] , and disentangled representations [159] . ...
doi:10.1109/jproc.2021.3058954
fatcat:jqg6jm2f35aynlszy6w5nsyem4
SAS: Self-Augmentation Strategy for Language Model Pre-training
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2106.07176v2 fatcat:5pihsqjmpndcblmlqf6kcxxfeuOther Versions
In this paper, we propose a self-augmentation strategy (SAS) where a single network is utilized for both regular pre-training and contextualized data augmentation for the training in later epochs. ...
In addition, SAS is a general strategy that can be seamlessly combined with many new techniques emerging recently or in the future, such as the disentangled attention mechanism from DeBERTa. ...
The Electric model is later proposed by Clark et al. (2020a) as an energy-based model to perform the cloze task (Taylor 1953 ) using noise-contrastive estimation (Gutmann and Hyvärinen 2012) . ...
arXiv:2106.07176v3
fatcat:6nat7wiebzgtvciy7qo7aoydmu
Deep Learning of Representations: Looking Forward
[chapter]
2013
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
This has led to various proposals for sampling from this implicitly learned density function, using Langevin and Metropolis-Hastings MCMC. ...
Whereas previous ways of dealing with the output bottleneck involved non-distributed word classes, we introduce a distributed representation for discrete word classes along with techniques to turn an apparently ...
He is also grateful for the funding support from NSERC, CIFAR, the Canada Research Chairs, and Compute Canada. ...
doi:10.1007/978-3-642-39593-2_1
fatcat:xad2okhdkrfbrhe4ilujsnoqlu
Representation Learning: A Review and New Perspectives
2013
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Although specific domain knowledge can be used to help design representations, learning with generic priors can also be used, and the quest for AI is motivating the design of more powerful representation-learning ...
This motivates longer-term unanswered questions about the appropriate objectives for learning good representations, for computing representations (i.e., inference), and the geometrical connections between ...
Acknowledgments The author would like to thank David Warde-Farley, Razvan Pascanu and Ian Goodfellow for useful feedback, as well as NSERC, CIFAR and the Canada Research Chairs for funding. ...
doi:10.1109/tpami.2013.50
pmid:23787338
fatcat:2ozfdsn2bjaa5jwtdovszpr5xa
Representation Learning: A Review and New Perspectives
[article]
2014
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2012 pre-print arXiv:1206.5538v1 fatcat:smr74p7mfvbdheadhxitaxllfeOther Versions
Although specific domain knowledge can be used to help design representations, learning with generic priors can also be used, and the quest for AI is motivating the design of more powerful representation-learning ...
This motivates longer-term unanswered questions about the appropriate objectives for learning good representations, for computing representations (i.e., inference), and the geometrical connections between ...
Acknowledgements The author would like to thank David Warde-Farley and Razvan Pascanu for useful feedback, as well as NSERC, CIFAR and the Canada Research Chairs for funding. ...
arXiv:1206.5538v3
fatcat:axiuzjr77zesvkaiewoh7cwmbq
"Here's to a Night of Drunken Mistakes": Exploring Experiences, Regrets, and Optimism in Young Adult Drinkers
2018
Substance Use & Misuse
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Laterality 2018; ePub(ePub): ePub. ...
Laterality 2018; ePub(ePub): ePub. ...
(Copyright 2018, Informa -Taylor and Francis Group) Hospital to school transition following traumatic brain injury: a qualitative longitudinal study -Todis B, McCart M, Glang A. ...
doi:10.1080/10826084.2018.1461227
pmid:29676652
fatcat:5oedsemlf5ex5pqdvaifhzpssq
The influence of action perception on object recognition: a developmental study
2007
Developmental Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Two experiments explored the existence and the development of relations between action representations and object representations. ...
While substantial priming effects were obtained for all age groups, they were especially important for the youngest participants. ...
We also want to thank Frédéric Michiels for miming the actions, Alain Perruchoud for creating the corresponding videos, Mathias Durrenberger for getting the program running and Aris Khan for his assistance ...
doi:10.1111/j.1467-7687.2007.00624.x
pmid:17973800
fatcat:conve3npyjhfhgk2sny7xzzlfe
« Previous
Showing results 1 — 15 out of 1,170 results