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Neural Temporal Point Processes: A Review [article]

Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
2021 arXiv   pre-print
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]

Haitao Lin, Lirong Wu, Guojiang Zhao, Pai Liu, Stan Z. Li
2022 arXiv   pre-print
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]

Shixiang Zhu, Shuang Li, Zhigang Peng, Yao Xie
2021 arXiv   pre-print
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]

Yizhou Zhang, Karishma Sharma, Yan Liu
2021 arXiv   pre-print
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

Shilpa Gite, Biswajeet Pradhan, Abdullah Alamri, Ketan Kotecha
2021 IEEE Access  
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

Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Stephan Günnemann
2021 Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence   unpublished
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

Lisa M. Hamm, Joanna Black, Shuan Dai, Benjamin Thompson
2014 Frontiers in Psychology  
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

Ken Nakayama
1985 Vision Research  
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]

Peter Yichen Chen, Maurizio Chiaramonte, Eitan Grinspun, Kevin Carlberg
2022 arXiv   pre-print
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

Marco A.F. Pimentel, David A. Clifton, Lei Clifton, Lionel Tarassenko
2014 Signal Processing  
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

Vijeta Sharma, Manjari Gupta, Ajai Kumar, Deepti Mishra
2021 IEEE Access  
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

Florent Lalys, Pierre Jannin
2013 International Journal of Computer Assisted Radiology and Surgery  
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

Alejandra Ciria, Guido Schillaci, Giovanni Pezzulo, Verena V. Hafner, Bruno Lara
2021 Neural Computation  
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  
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

Martin A. Rohrmeier, Stefan Koelsch
2012 International Journal of Psychophysiology  
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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