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Neural Temporal Point Processes: A Review
[article]
2021
arXiv
pre-print
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Temporal point processes (TPP) are probabilistic generative models for continuous-time event sequences. ...
Neural TPPs combine the fundamental ideas from point process literature with deep learning approaches, thus enabling construction of flexible and efficient models. ...
Temporal point processes (TPP) are probabilistic models for such event data [Daley and Vere-Jones, 2007] . ...
arXiv:2104.03528v5
fatcat:xze2b3kzefe3bmnv27so4ujdgq
Exploring Generative Neural Temporal Point Process
[article]
2022
arXiv
pre-print
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In this work, we try to fill the gap by designing a unified generative framework for neural temporal point process (GNTPP) model to explore their feasibility and effectiveness, and further improve models ...
Temporal point process (TPP) is commonly used to model the asynchronous event sequence featuring occurrence timestamps and revealed by probabilistic models conditioned on historical impacts. ...
We thank a lot to all the reviewers who are responsible, careful and professional in TMLR for their valuable and constructive comments. ...
arXiv:2208.01874v2
fatcat:45oqfvcqlfefrct57bkkvuv66i
Imitation Learning of Neural Spatio-Temporal Point Processes
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:1906.05467v3 fatcat:eipavv6lkfgbthbkyus6z26msmOther Versions
We present a novel Neural Embedding Spatio-Temporal (NEST) point process model for spatio-temporal discrete event data and develop an efficient imitation learning (a type of reinforcement learning) based ...
Despite the rapid development of one-dimensional temporal point processes for discrete event data, the study of spatial-temporal aspects of such data is relatively scarce. ...
Good performance has been achieved for modeling temporal point processes [6] and marked temporal point processes [7] . ...
arXiv:1906.05467v4
fatcat:5hpjnqgadjb5rmsnu7gmdkquzm
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
[article]
2021
arXiv
pre-print
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Therefore, in this paper, we propose a coordination detection framework incorporating neural temporal point process with prior knowledge such as temporal logic or pre-defined filtering functions. ...
Specifically, when modeling the observed data from social media with neural temporal point process, we jointly learn a Gibbs-like distribution of group assignment based on how consistent an assignment ...
Also, we are very thankful for the comments and suggestions from our anonymous reviewers. ...
arXiv:2110.15454v1
fatcat:ugt5djpvzffy3gbnqgirpfbq6e
ADMT: Advanced Driver's Movement Tracking system using Spatio-temporal interest points and maneuver anticipation using deep neural networks
2021
IEEE Access
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It can handle the detection of interest points from a video to process the Spatio-temporal domain information effectively [29] [30] . Hence, it has become adaptable for the research problem.
C. ...
The feature extraction from the Spatio-temporal video data is performed using the Spatio-Temporal Interest Points (STIP) method [16] [17] . ...
doi:10.1109/access.2021.3096032
fatcat:mcuy36ydyfaynp5itq6ft6txvi
Neural Temporal Point Processes: A Review
2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
unpublished
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Temporal point processes (TPP) are probabilistic generative models for continuous-time event sequences. ...
Neural TPPs combine the fundamental ideas from point process literature with deep learning approaches, thus enabling construction of flexible and efficient models. ...
Temporal point processes (TPP) are probabilistic models for such event data [Daley and Vere-Jones, 2007] . ...
doi:10.24963/ijcai.2021/623
fatcat:6sfxzbpzfje57hr2gov3qth4am
Global processing in amblyopia: a review
2014
Frontiers in Psychology
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Here, we review the current literature on global processing deficits in observers with either strabismic, anisometropic, or deprivation amblyopia. ...
A range of global processing tasks have been used to investigate the extent of the cortical deficit in amblyopia including: global motion perception, global form perception, face perception, and biological ...
Second-order temporal processing Temporal processing of second-order stimuli shows a different pattern. ...
doi:10.3389/fpsyg.2014.00583
pmid:24987383
pmcid:PMC4060804
fatcat:bt6irqf7fbehnm7ci5alb4ut7a
Biological image motion processing: A review
1985
Vision Research
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Parallel and serial processing within an early motion system: a skeletal model Random dot stimuli D ImAX Dm, ...
as a proprioceptive sense (5) Motion as a stimulus to drive eye movements (6) Motion as required for pattern vision (7) Image motion processing as useful for perceiving real moving objects Multiplicity ...
Such a model implies that one could compute velocity by taking a temporal derivative of the luminance at a point and dividing it by the spatial derivative at the same point. ...
doi:10.1016/0042-6989(85)90171-3
pmid:3895725
fatcat:fbyrcamgfjautc5nnoeuk7afgm
Model reduction for the material point method via an implicit neural representation of the deformation map
[article]
2022
arXiv
pre-print
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This work proposes a model-reduction approach for the material point method on nonlinear manifolds. ...
At each time step, these techniques: (1) Calculate full-space kinematics at quadrature points, (2) Calculate the full-space dynamics for a subset of 'sample' material points, and (3) Calculate the reduced-space ...
Consequently, in the process of numerically evaluating the integral (15) , we can use a quadrature rule defined either on the Lagrangian quadrature points or the Eulerian quadrature points. ...
arXiv:2109.12390v2
fatcat:ot7kfp5oqjekzjqw52q4g3qkqi
A review of novelty detection
2014
Signal Processing
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Neural network-based approaches Several types of neural networks have been proposed for novelty detection, a review of which can be found in [27] . ...
The rejected data points are collected in a "bin" for further processing. Post-processing of this filtered output has the goal of identifying clusters. ...
doi:10.1016/j.sigpro.2013.12.026
fatcat:ha6kc4bzhbajxbo2mdyh5cw5hu
Video Processing using Deep learning Techniques: A Systematic Literature Review
2021
IEEE Access
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This paper aims to present a Systematic Literature Review (SLR) on video processing using deep learning to investigate the applications, functionalities, techniques, datasets, issues, and challenges by ...
However, a combined study is still unexplored. ...
Figure 3 shows the concept of a two-stream convolutional neural network for video processing in a Spatio-temporal manner.
2) DNN BASED APPROACH A deep neural network is considered an advanced form ...
doi:10.1109/access.2021.3118541
fatcat:oadlu4uyirc2tanqrixz3sn6ny
Surgical process modelling: a review
2013
International Journal of Computer Assisted Radiology and Surgery
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This methodological review was obtained from a search using Google Scholar on the specific keywords: "surgical process analysis", "surgical process model", and "surgical workflow analysis". ...
In this paper, we present a review of the literature dealing with SPM. ...
Temporal modelling allows the duration of each step and of the entire process during its execution to be evaluated. ...
doi:10.1007/s11548-013-0940-5
pmid:24014322
fatcat:sdhhofpypvdsloklojucsqdlh4
Predictive Processing in Cognitive Robotics: A Review
2021
Neural Computation
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Furthermore, it aims at unifying perception, cognition, and action as a single inferential process. ...
This framework turns the traditional view of perception upside down, claiming that the main flow of information processing is realized in a top-down, hierarchical manner. ...
Finally, Ahmadi and Tani (2017) propose a multiple timescale recurrent neural network (MTRNN), which consists of multiple levels of subnetworks with specific temporal constraints on each layer. ...
doi:10.1162/neco_a_01383
pmid:34496394
fatcat:hnkc5rtcf5dpljoriyg7ueg5by
Understanding Predictive Processing. A Review
2021
Avant
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The purpose of this paper is to provide a systematic review of the Predictive Processing framework (hereinafter PP) and to identify its basic theoretical difficulties. ...
Thus, this review not only discusses PP, but also provides an assessment of the condition of this research framework in the light of the hopes placed on it by many researchers. ...
Special thanks are due to the editors of the "Avant" journal for inviting me to write this review. ...
doi:10.26913/avant.2021.01.04
fatcat:num5wrukabbfxcmuusua5rv4fm
Predictive information processing in music cognition. A critical review
2012
International Journal of Psychophysiology
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We review the scope and limits of theoretical accounts of musical prediction with respect to feature-based and temporal prediction. ...
Neuroscientific results regarding the early right-anterior negativity (ERAN) and mismatch negativity (MMN) reflect expectancy violations on different levels of processing complexity, and provide some neural ...
Acknowledgements We would like to thank Moritz Lehne, Renzo Torrecuso and two reviewers for many helpful comments on the manuscript. ...
doi:10.1016/j.ijpsycho.2011.12.010
pmid:22245599
fatcat:nj6rxxei6bcavf3epe2z7loh2u
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