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PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited...
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Debugging convergence problems in probabilistic programs via program representation learning with SixthSense
Probabilistic programming aims to open the power of Bayesian reasoning to software developers and scientists, but identification of problems during...
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Interactive group decision making method based on probabilistic hesitant Pythagorean fuzzy information representation
Interactive group evaluation is a decision-making method to obtain group consensus by constantly modifying the initial weight of experts....
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Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network
In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, many...
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Lifting in Support of Privacy-Preserving Probabilistic Inference
Privacy-preserving inference aims to avoid revealing identifying information about individuals during inference. Lifted probabilistic inference works...
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Probabilistic Approach to Good Old-Fashioned Artificial Intelligence
AbstractThe paper proposes the use of a probabilistic knowledge-extraction mechanism to resume the use of good old-fashioned artificial intelligence....
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Generalised Diffusion Probabilistic Scale-Spaces
Diffusion probabilistic models excel at sampling new images from learned distributions. Originally motivated by drift-diffusion concepts from...
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Dissertation Abstract: Taming Exact Inference in Temporal Probabilistic Relational Models
Processes in our world are of a temporal probabilistic relational nature. An epidemic is an example of such a process. This dissertation abstract...
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Probabilistic multiplicative unbalanced linguistic game using linguistic cloud model
In many game theoretic environments, the precise crisp values of payoffs are not always easy to gather as real-life decision-making problems are not...
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A probabilistic generative model for tracking multi-knowledge concept mastery probability
Knowledge tracing aims to track students’ knowledge status over time to predict students’ future performance accurately. In a real environment,...
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A probabilistic meta-heuristic optimisation algorithm for image multi-level thresholding
The spread of the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) which causes CoronaVirus Disease 2019 (COVID-19) has challenged many...
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A probabilistic spatio-temporal neural network to forecast COVID-19 counts
Geo-referenced and temporal data are becoming more and more ubiquitous in a wide range of fields such as medicine and economics. Particularly in the...
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Knowledge representation and acquisition for ethical AI: challenges and opportunities
Machine learning (ML) techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as...
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Probabilistic root finding in code-based cryptography
Probabilistic algorithms for finding roots of polynomials have not been applied to code-based cryptography before. One obstacle is their non-constant...
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Probabilistic Model-Building Genetic Algorithms
The previous chapter showed that variation operators in genetic and evolutionary algorithms can be replaced by learning a probabilistic model of...
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Probabilistic Latent Semantic Analysis
This chapter introduces the models of Probabilistic Latent Semantic Analysis (PLSA), including generative and co-occurrence models, and then...
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Learning Deep Patch representation for Probabilistic Graphical Model-Based Face Sketch Synthesis
Face sketch synthesis has a wide range of applications in both digital entertainment and law enforcement. State-of-the-art examplar-based methods...
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A Cognitive Uncertainty Calculation Method Based on Probabilistic Linguistic Term Set and Applications in Geopolitical Risk Assessment
Risk is essentially uncertain, including objective uncertainty of natural attributes and subjective uncertainty of human cognition. The latter is...
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Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks
In the dynamic smart grid landscape, accurate probabilistic forecasting of electric load is critical. This paper presents a novel 24-hour-ahead...
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Trilateration-based indoor localization utilizing the matrix completion method by probabilistic matrix factorization and stochastic gradient
This research presents an enhanced indoor positioning system using Received Signal Strength Indicator (RSSI) values and probabilistic matrix...
