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Direct Inference and Probabilistic Accounts of Induction
Schurz (
2019 , ch. 4) argues that probabilistic accounts of induction fail. In particular, he criticises probabilistic accounts of induction that...
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Direct current field enhanced boronizing of stainless steels and predictive performance of diffusion kinetics, deep neural network, and adaptive neuro-fuzzy inference system on boride layer thickness
The boronizing process is a thermochemical surface treatment related to diffusion and requires high temperature and long-period soaking time. The...
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PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorization
Inferring gene regulatory networks (GRNs) from single-cell data is challenging due to heuristic limitations. Existing methods also lack estimates of...
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Multi-Agent Systems for Collaborative Inference Based on Deep Policy Q-Inference Network
This study tackles the problem of increasing efficiency and scalability in deep neural network (DNN) systems by employing collaborative inference, an...
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Is Fisher inference inferior to Neyman inference for policy analysis?
The increasing computational power has led to an increasing interest in Fisher’s test in social science. As the Fisher and Neyman inference are based...
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Causal Inference of Direct Email Advertising Effects Using ID-POS Data of an Electronics Store
In this study, we estimate the causal effect of direct promotional email advertising when an RCT could not be performed by only using observational...
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High-dimensional robust inference for censored linear models
Due to the direct statistical interpretation, censored linear regression offers a valuable complement to the Cox proportional hazards regression in...
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Causal inference in the medical domain: a survey
Causal inference is considered a crucial topic in the medical field, as it enables the determination of causal effects for medical treatments through...
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Variational Inference
Variational inference has become an important research topic in machine learning. It transforms a posterior reasoning problem into an optimization...
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A general model-based causal inference method overcomes the curse of synchrony and indirect effect
To identify causation, model-free inference methods, such as Granger Causality, have been widely used due to their flexibility. However, they have...
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Belief inference for hierarchical hidden states in spatial navigation
Uncertainty abounds in the real world, and in environments with multiple layers of unobservable hidden states, decision-making requires resolving...
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Causal inference for time series
Many research questions in Earth and environmental sciences are inherently causal, requiring robust analyses to establish whether and how changes in...
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Approximations of System W Between c-Inference, System Z, and Lexicographic Inference
Inductive inference operators have been introduced to formalize the process of completing a conditional belief base to a full inference relation. In...
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Infinite frequency principles of direct inference
According to an infinite frequency principle, it is rational, under certain conditions, to set your credence in an outcome to the limiting frequency...
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Collective relational inference for learning heterogeneous interactions
Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions....
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Strategy inference using the maximum likelihood estimation in the iterated prisoner’s dilemma game
The iterated prisoner’s dilemma game has shown how cooperation evolves based on direct reciprocity. In the course of iterated interactions, a player...
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Adaptive data-driven subsampling for efficient neural network inference
In this paper we present a novel data-driven subsampling method that can be seamlessly integrated into any neural network architecture to identify...
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The insight of why: Causal inference in Earth system science
The utilization of big Earth data has provided insights into the planet we inhabit in unprecedented dimensions and scales. Unraveling the concealed...
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Bayesian inference elucidates fault-system anatomy and resurgent earthquakes induced by continuing saltwater disposal
An earthquake sequence in western Canada exhibits resurgent aftershocks, possibly in response to persistent, post-mainshock saltwater disposal. Here,...
