Filters








153,598 Hits in 7.8 sec

Mutation effect estimation on protein–protein interactions using deep contextualized representation learning

Guangyu Zhou, Muhao Chen, Chelsea J T Ju, Zheng Wang, Jyun-Yu Jiang, Wei Wang
2020 NAR Genomics and Bioinformatics  
We present an end-to-end deep learning framework, MuPIPR (Mutation Effects in Protein–protein Interaction PRediction Using Contextualized Representations), to estimate the effects of mutations on PPIs.  ...  Multi-layer perceptron regressors are applied to the protein pair representations to predict the quantifiable changes of PPI properties upon mutations.  ...  ACKNOWLEDGEMENTS We appreciate the anonymous reviewers for their insightful comments and suggestions to help us improve this paper. FUNDING  ... 
doi:10.1093/nargab/lqaa015 pmid:32166223 pmcid:PMC7059401 fatcat:dihlblu3ifg6vayxmxr4ikomry

Lexical category acquisition is facilitated by uncertainty in distributional co-occurrences

Giovanni Cassani, Robert Grimm, Walter Daelemans, Steven Gillis, Eva María Rosa Martínez
2018 PLoS ONE  
This indicates that words are easier to categorize in the face of uncertainty: categorization works best for words which are frequent, diverse, and hard to predict given the co-occurring contexts.  ...  First, word-context co-occurrence counts were collected using corpora of transcribed English child-directed speech.  ...  We thank Stéphan Tulkens and two anonymous reviewers for the useful comments on the manuscript, Antal van den Bosch and Dominiek Sandra for useful feedback about the conceptualization of this work.  ... 
doi:10.1371/journal.pone.0209449 pmid:30592738 pmcid:PMC6310260 fatcat:wkwk5uxyvjfwzlbn2j6xzo4tqa

When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes [article]

Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman
2021 arXiv   pre-print
Our model captures useful information for contextual reasoning, enabling human-level performance and better robustness in out-of-context conditions compared to baseline models across OCD and other out-of-context  ...  We conducted a series of experiments to gain insights into the impact of contextual cues on both human and machine vision using OCD.  ...  We thank Leonard Tang, Jeremy Schwartz, Seth Alter, Xavier Puig, Hanspeter Pfister, Jen Jen Chung, and Cesar Cadena for useful discussions and support.  ... 
arXiv:2104.02215v2 fatcat:ocofxdskljfi5hrpfgeaa64y5a

Co-occurrence graphs

Louis-Philippe Morency
2009 Proceedings of the Workshop on Use of Context in Vision Processing - UCVP '09  
In this paper we describe how contextual information from other participants can be used to predict visual feedback and improve recognition of head gestures in multiparty interactions (e.g., meetings).  ...  Using a discriminative approach to multi-modal integration, our contextual representation using co-occurrence graph improves head gesture recognition performance on a publicly available dataset of multi-party  ...  Section 4 introduces co-occurrence graphs and Section 5 describes how to use them to encode contextual information.  ... 
doi:10.1145/1722156.1722160 fatcat:fhxhajtelbf6zeuugkkg57k7ia

A Multi-level Contextual Model for Person Recognition in Photo Albums

Haoxiang Li, Jonathan Brandt, Zhe Lin, Xiaohui Shen, Gang Hua
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Through experiments, we show that the information available at each of these distinct contextual levels provides complementary cues as to person identities.  ...  By exploiting this shared contextual information, we are able to reduce the identity search space and exploit higher intra-personal appearance consistency within photo groups.  ...  This work is also partly supported by US National Science Foundation Grant IIS 1350763 and GH's start-up funds from Stevens Institute of Technology.  ... 
doi:10.1109/cvpr.2016.145 dblp:conf/cvpr/LiB0SH16 fatcat:tdqorm3phnhczignxtvddregt4

Mapping of contextual modulation in the population response of primary visual cortex

David M. Alexander, Cees Van Leeuwen
2009 Cognitive Neurodynamics  
The mapping of contextual features onto the orientation pinwheel has a form that recapitulates the organization of the visual field: an iso-orientation patch within the pinwheel also responds to extra-RF  ...  We review the evidence of long-range contextual modulation in V1.  ...  Let us now turn to the singularity prediction. Vanduffel et al. (2002) reported that the relationship between CO blobs and orientation selectivity changes as a function of eccentricity.  ... 
doi:10.1007/s11571-009-9098-9 pmid:19898958 pmcid:PMC2837531 fatcat:riuus626brfa5ok4qdgfwt6qyi

Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization

Lourenco V. Pato, Renato Negrinho, Pedro M. Q. Aguiar
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Rescoring is done by conditioning on contextual information from the entire set of detections: their confidences, predicted classes, and positions.  ...  In this setting, we use a bidirectional RNN with attention for contextual rescoring and introduce a training target that uses the IoU with ground truth to maximize AP for the given set of detections.  ...  In the following section, we train a rescoring model that uses contextual information to predict these target confidences.  ... 
doi:10.1109/cvpr42600.2020.01462 dblp:conf/cvpr/PatoNA20 fatcat:gyegpwf7prbmdgsxgccgcz3iiq

Whatever after Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search

Markus Conci, Martina Zellin, Hermann J. Müller
2012 Frontiers in Psychology  
can be adjusted from one instance to the next, with relatively transient switch costs after a change (Maljkovic and Nakayama, 1994; Found and Müller, 1996) .  ...  Thus, some evidence, which seems to relate in particular to short-term predictions, suggests that expectations are dynamically adjustable based on encountering only a few instances.  ...  Acknowledgment This work was supported by a Deutsche Forschungsgemeinschaft (DFG) Project (CO 1002/1-1) grant.  ... 
doi:10.3389/fpsyg.2012.00409 pmid:23087662 pmcid:PMC3475347 fatcat:evyppwvigzda7bekhrnd7dxbk4

Predicting Co-Changed Files: An External, Conceptual Replication

Ayşe TOSUN, Betül Romero
2019 Celal Bayar Universitesi Fen Bilimleri Dergisi  
s prior work on predicting co-changed files.  ...  Although it is practically more useful, predicting all files that will be co-changed together during a commit is more challenging than predicting whether a particular file will be changed in that commit  ...  [9] conducted a study to improve the prediction of build co-changes by using the detailed information on source code changes and commit categories.  ... 
doi:10.18466/cbayarfbe.489291 fatcat:zxpjeomblngkjc7qnfwtcglfy4

Autistic Traits Differently Account for Context-Based Predictions of Physical and Social Events

Valentina Bianco, Alessandra Finisguerra, Sonia Betti, Giulia D'Argenio, Cosimo Urgesi
2020 Brain Sciences  
Autism is associated with difficulties in making predictions based on contextual cues.  ...  phase, in which visual information was impoverished by early occlusion of video display, thus forcing participants to rely on previously learned context-based associations.  ...  Using the same action prediction task of this study, a recent study [20] showed that children with typical development were able to use previously learned contextual information to successfully predict  ... 
doi:10.3390/brainsci10070418 pmid:32630346 pmcid:PMC7407668 fatcat:qihedlzoszhcphigd6zbyou4ju

ContextCare: Incorporating Contextual Information Networks to Representation Learning on Medical Forum Data

Stan Zhao, Meng Jiang, Quan Yuan, Bing Qin, Ting Liu, ChengXiang Zhai
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
To alleviate the network sparseness, ContextCare adopts regularizations from rich contextual information networks including a symptom co-occurrence network and a disease evolution network.  ...  , disease category prediction and disease clustering.  ...  To make use of those two networks as contextual information for accurate disease prediction, we propose a novel method, CONTEXTCARE, to integrate the three networks of different aspects but rich information  ... 
doi:10.24963/ijcai.2017/489 dblp:conf/ijcai/ZhaoJYQLZ17 fatcat:33w6kiogafdlpcivrnuxqgutdu

The Role of Context in Affective Behavior Understanding [chapter]

Louis-Philippe Morency
2013 Social Emotions in Nature and Artifact  
Head nods are used for displaying agreement, grounding information or during turn-taking [7, 8] .  ...  During multi-party interactions such as in meetings, information is exchanged between participants using both audio and visual channels.  ...  The main idea is to use this existing information to predict when visual feedback gestures from the user are likely.  ... 
doi:10.1093/acprof:oso/9780195387643.003.0009 fatcat:32x3i43b5rc43fl4nojmrhu2lm

Gender Bias in Contextualized Word Embeddings [article]

Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, Kai-Wei Chang
2019 arXiv   pre-print
In this paper, we quantify, analyze and mitigate gender bias exhibited in ELMo's contextualized word vectors.  ...  Finally, we explore two methods to mitigate such gender bias and show that the bias demonstrated on WinoBias can be eliminated.  ...  Unequal Treatment of Gender To test how ELMo embeds gender information in contextualized word embeddings, we train a classifier to predict the gender of entities from occupation words in the same sentence  ... 
arXiv:1904.03310v1 fatcat:dow5oen2tzbcnm2r5piwekqmjy

Comparing the Effect of Contextualized Versus Generic Automated Feedback on Students' Scientific Argumentation

Margarita Olivera‐Aguilar, Hee‐Sun Lee, Amy Pallant, Vinetha Belur, Matthew Mulholland, Ou Lydia Liu
2022 ETS Research Report Series  
This study uses a computerized formative assessment system that provides automated scoring and feedback to help students write scientific arguments in a climate change curriculum.  ...  Classes were randomly assigned to the contextualized feedback condition (227 students from 11 classes) or to the generic feedback condition (138 students from 9 classes).  ...  Students are then asked to predict what would happen if CO 2 concentrations were to decrease in the atmosphere.  ... 
doi:10.1002/ets2.12344 fatcat:porft5zfffc3fn3trv2upr4bly

Using contextual analysis method to predict new energy development of Hohhot

LI Changqing, DUAN Wei
2011 Energy Procedia  
Contextual analysis method is used to predict new energy development of Hohhot from 2010 to 2020.  ...  Practice shows that the contextual analysis for the prediction and policy formulation will have a practical significance.  ...  Using contextual analysis method to predict new energy development of Hohhot4.1.  ... 
doi:10.1016/j.egypro.2011.03.037 fatcat:sif3hartrve3bamsxpgbwgycde
« Previous Showing results 1 — 15 out of 153,598 results