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Learning Perceptual Inference by Contrasting
[article]
2019
arXiv
pre-print
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Combining all the elements, we propose the Contrastive Perceptual Inference network (CoPINet) and empirically demonstrate that CoPINet sets the new state-of-the-art for permutation-invariant models on ...
Inspired by cognitive studies, we equip our model with a simple inference module that is jointly trained with the perception backbone. ...
Learning Perceptual Inference by Contrasting
Chi Zhang?,1,4 , Baoxiong Jia? ...
arXiv:1912.00086v1
fatcat:invw7cwzu5asdgdhirimn4ysqa
SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Deraining
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2111.08892v1 fatcat:d6r7ftpgdndm3lri54hivsq7mi
Furthermore, we introduce a perceptual contrastive loss (PCL) and a learned perceptual image similarity loss (LPISL) to regulate model learning. ...
To address this issue, in this paper, we present a segmentation-aware progressive network (SAPNet) based upon contrastive learning for single image deraining. ...
contrastive loss (PCL), dilation, learning rate decay and learned perceptual image similarity loss (LPISL). ...
arXiv:2111.08892v2
fatcat:giv3wx2h3vbk3mk7hh2azde3fe
The role of abstraction in non-native speech perception
2014
Journal of Phonetics
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We argue that these results support a view of perceptual reorganization as the consequence of learners' hierarchical inductive inferences about the structure of the language's sound system: infants not ...
Specifically, we show that the knowledge of a language with short and long vowel categories leads to enhanced discrimination of non-native consonant length contrasts. ...
This research was supported by NIH Training Grant T32-DC-000041 from the Center for Research in Language at UC San Diego to B.P. and NIH Training Grant T32-DC000035 from the Center for Language Sciences ...
doi:10.1016/j.wocn.2014.07.001
pmid:25197153
pmcid:PMC4153394
fatcat:alp2u74iong2bmvjbh552zrq4m
Perceptual learning as improved probabilistic inference in early sensory areas
2011
Nature Neuroscience
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Therefore, the key to the neural basis of perceptual learning may have less to do with how tuning curves change and more to do with how the connectivity is adjusted to improve the inference performed by ...
Here we argue that perceptual learning might be due to improved probabilistic inference induced by changes at the sensory processing stage rather than at the decision stage (at least in the case of orientation ...
doi:10.1038/nn.2796
pmid:21460833
pmcid:PMC3329121
fatcat:pyzbudr37baodejtqnoxulvh4e
Hybrid Predictive Coding: Inferring, Fast and Slow
[article]
2022
arXiv
pre-print
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It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors" - the differences between predicted and observed data. ...
We demonstrate that our hybrid predictive coding model combines the benefits of both amortized and iterative inference -- obtaining rapid and computationally cheap perceptual inference for familiar data ...
In contrast, predictive coding suggests that the brain solves perception by modelling how perceptual representations z generate sensory data x, which is a fundamentally top-down process. ...
arXiv:2204.02169v2
fatcat:ay3micqq4bdxjf4u65edozinyq
Belief states and categorical-choice biases determine reward-based learning under perceptual uncertainty
[article]
2020
biorxiv/medrxiv
pre-print
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We found that both factors influenced participants' behavior, which was similarly captured in Bayesian-inference and Q-learning models. ...
In natural settings, learning and decision making often takes place under considerable perceptual uncertainty. ...
., R.B. was supported by the International Max Planck Research School LIFE, Berlin, Germany.
CRediT author statement ...
doi:10.1101/2020.09.18.303495
fatcat:x5veamvwcfajzgzrgpobppzqwy
Choice variability and suboptimality in uncertain environments
2016
Current Opinion in Behavioral Sciences
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This variability is usually hypothesized as noise at the periphery of inferential processes, namely sensory noise in perceptual tasks and stochastic exploration in reward-guided learning, or as suboptimal ...
Making decisions under uncertainty, from perceptual judgments to reward-guided choices, requires combining multiple pieces of decision-relevant information -a cognitive process modeled as statistical inference ...
By contrast, the intrinsic stochasticity of inference imprecisions (i.e., the 'variance' term) reflects the effective precision at which inference is performed. ...
doi:10.1016/j.cobeha.2016.07.003
fatcat:2f2vizehizce5dy6fgdupo5o4i
The Neural Correlates of Hierarchical Predictions for Perceptual Decisions
2018
Journal of Neuroscience
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By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. ...
Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. ...
Crucially, here, we were interested in such perceptual expectations or priors that are formed by associative learning; that is, the subjects' continuously updated inference on the probabilistic coupling ...
doi:10.1523/jneurosci.2901-17.2018
pmid:29712780
pmcid:PMC6596123
fatcat:4qmdnehowra4xp4dpndrauc5wm
A Philosophical Analysis of the Updating Rule in a Bayesian Perceptual Learning Model
2021
Annals of the Japan Association for Philosophy of Science
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Human object perception is now widely called Bayesian inference or statistical inference, while obtaining a Bayesian quantitative model of human perceptual learning has become a primary goal for the consciousness ...
Helmholtz's idea of perception as unconscious inference is formalized by Bayes' theorem. ...
Introduction Bayesian models of human perceptual learning have been widely studied in re-cent times. Helmholtz's idea of perception as unconscious inference is formalized by Bayes' theorem. ...
doi:10.4288/jafpos.30.0_85
fatcat:esd2m5j5vza6zblrhxx6ehkywa
Electrophysiological indices reflect switches between Bayesian and heuristic strategies in perceptual learning
[article]
2017
bioRxiv
pre-print
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These findings suggest that use of Bayesian inference in perceptual learning may depend on motivational state. ...
We recorded electroencephalography from 23 participants performing a perceptual learning task with both monetary and a non-monetary instructive feedback conditions. ...
As a result, learning was necessarily affected by perceptual uncertainty regarding the identity of the chosen contrast. ...
doi:10.1101/183665
fatcat:h7cf5xmiczey3lrld7roxcmiia
Page 800 of Psychological Abstracts Vol. 93, Issue 3
[page]
2006
Psychological Abstracts
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by the inference learning task demands in Experiment 1. ...
—This research’s purpose was to contrast the repre- sentations resulting from learning of the same categories by either classifying instances or inferring instance features. ...
Delusions and the Role of Beliefs in Perceptual Inference
2013
Journal of Neuroscience
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Here, we empirically validated a neurocognitive model that explains both the formation and the persistence of delusional beliefs in terms of altered perceptual inference. ...
Delusional ideation was associated with less perceptual stability, but a stronger belief-induced bias on perception, paralleled by enhanced functional connectivity between frontal areas that encoded beliefs ...
. • Delusions and Perceptual Inference ...
doi:10.1523/jneurosci.1778-13.2013
pmid:23966692
pmcid:PMC6618656
fatcat:6pgrpagbdbbsxdjymqczbdu5b4
Brain-Based Mechanisms Underlying Causal Reasoning
[chapter]
2009
Neural Correlates of Thinking
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This can be contrasted with casual inference, which demands the learning of causal associations based on covariation experience. ...
to infer basic characteristics about the objects that may be in conflict with the perceptual experience. ...
doi:10.1007/978-3-540-68044-4_16
fatcat:qyhk42nlwvhplkcdckxn46vdhe
Perceptual Learning: Cortical Changes When Cats Learn a New Trick
2010
Current Biology
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Upon a 'correct' response, the luminance contrast of the presented stimuli decreased. ...
The perceptual learning experiment of Hua et al. [2]. In training, a cat had to choose the one stimulus that contained the same orientation as the pre-determined orientation. ...
The results provide compelling evidence for changes in V1 neurons in association with perceptual learning. What can and what cannot be inferred from the results? ...
doi:10.1016/j.cub.2010.05.004
pmid:20619806
pmcid:PMC3815644
fatcat:omm64eaynvg7hoimcjmuyyqouu
Reinforcement of perceptual inference: reward and punishment alter conscious visual perception during binocular rivalry
2014
Frontiers in Psychology
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We conclude that perceptual inference is an adaptive process that is shaped by its consequences. ...
In two behavioral experiments, we used binocular rivalry to examine whether perceptual inference can be influenced by the association of perceptual outcomes with reward or punishment, respectively, in ...
According to our hypothesis that perceptual inference is shaped by instrumental learning, we expected that reward should bias inference toward the associated perceptual outcome, leading to increased dominance ...
doi:10.3389/fpsyg.2014.01377
pmid:25520687
pmcid:PMC4253824
fatcat:rjiuvx5qxffovjijd7fd546srm
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