wanyu/IteraTeR_v2 huggingface dataset:
Original:  Thereby, we can (a) quantify the effects of recent governmental measures to mitigating the disease spread, and (b) incorporate the corresponding change points to forecast future scenarios and case numbers.
Revised:  Thereby, we can quantify the effect of interventions, and we can incorporate the corresponding change points to forecast future scenarios and case numbers.
Edit intent: clarity
Original:  Thereby, we can (a) quantify the effects of recent governmental measures to mitigating the disease spread, and (b) incorporate the corresponding change points to forecast future scenarios and case numbers.
Revised:  Thereby, we can (a) quantify the effects of recent governmental measures to mitigating the disease spread, and (b) incorporate the corresponding change points into forecasts of future scenarios and case numbers.
Edit intent: style
Original:  If protein folding could be solved, it would lead to significant advances in molecular biology, and technological development in areas such as drug discovery and catalyst design.
Revised:  If protein folding could be solved, it would lead to significant advances in molecular biology, drug discovery and catalyst design.
Edit intent: clarity
Original:  As a hard combinatorial optimisation problem, protein folding has been studied as a potential target problem for adiabatic quantum computing .
Revised:  As a hard combinatorial optimisation problem, it has been studied as a potential target problem for adiabatic quantum computing .
Edit intent: clarity
Original:  As a hard combinatorial optimisation problem, protein folding has been studied as a potential target problem for adiabatic quantum computing .
Revised:  As a hard combinatorial optimisation problem, protein folding has been studied as a potential target problem for quantum annealing .
Edit intent: clarity
Original: A recent line of studies has focused on the infinite width limit of deep neural networks (DNNs) where, under a certain deterministic training protocol, the DNN outputs are related to a Gaussian Process (GP ) known as the Neural Tangent Kernel (NTK) . However, finite-width DNNs differ from GPs quantitatively and for CNNs the difference may be qualitative .
Revised: A recent line of works studied wide deep neural networks (DNNs) where, under a certain deterministic training protocol, the DNN outputs are related to a Gaussian Process (GP ) known as the Neural Tangent Kernel (NTK) . However, finite-width DNNs differ from GPs quantitatively and for CNNs the difference may be qualitative .
Edit intent: clarity
Original: A recent line of studies has focused on the infinite width limit of deep neural networks (DNNs) where, under a certain deterministic training protocol, the DNN outputs are related to a Gaussian Process (GP ) known as the Neural Tangent Kernel (NTK) . However, finite-width DNNs differ from GPs quantitatively and for CNNs the difference may be qualitative .
Revised: A recent line of studies has focused on the infinite width limit of deep neural networks (DNNs) by approximating them as Gaussian Processes (GPs). A DNN trained with gradient flow was shown to map to a GP governed by the Neural Tangent Kernel (NTK) . However, finite-width DNNs differ from GPs quantitatively and for CNNs the difference may be qualitative .
Edit intent: clarity
Original:  Here we present a DNN training protocol involving noise whose outcome is mappable to a certain non-Gaussian stochastic process.
Revised:  Here we consider a DNN training protocol involving noise whose outcome is mappable to a certain non-Gaussian stochastic process.
Edit intent: clarity
Original:  An analytical framework is then introduced to analyze this resulting non-Gaussian process, whose deviation from a GP is controlled by the finite width.
Revised:  An analytical framework is then introduced to analyze this non-Gaussian process, whose deviation from a GP is controlled by the finite width.
Edit intent: clarity
Original:  Our work extends upon previous relations between DNNs and GPs in several ways: (a ) In the infinite width limit, it establishes a mapping between DNNs and a GP different from the NTK. ( b) It allows computing analytically the general form of the finite width correction (FWC) for DNNs with arbitrary activation functions and depth and further provides insight on the magnitude and implications of these FWCs.
Revised:  Our work extends upon previous relations between DNNs and GPs in several ways: (a ) In the infinite width limit, it establishes a mapping between DNNs and a GP different from the NTK. ( ii) We provide a general analytical form for the finite width correction (FWC) for DNNs with arbitrary activation functions and depth and further provides insight on the magnitude and implications of these FWCs.
Edit intent: coherence
Original:  (iii) We flesh-out algebraically how these FWCs can improve the performance of finite convolutional neural networks (CNNs) relative to their GP counterparts on image classification tasks.
Revised:  (iii) We flesh out algebraically how these FWCs can improve the performance of finite convolutional neural networks (CNNs) relative to their GP counterparts on image classification tasks.
Edit intent: fluency
Original:  There are three versions of the operational semantics of the pi-calculus , called reduction, late, and early .
Revised:  Various operational semantics of the pi-calculus , called reduction, late, and early .
Edit intent: clarity
Original: We introduce a new problem of retrieving 3D models that are not just similar but are deformable to a given query shape .
Revised: We introduce a new problem of retrieving 3D models that are not just similar but are deformable to a given query shape .
Edit intent: fluency
Original: We introduce a new problem of retrieving 3D models that are not just similar but are deformable to a given query shape .
Revised: We introduce a new problem of retrieving 3D models that are deformable to a given query shape .
Edit intent: coherence
Original:  We then present a novel deep deformation-aware embedding to solve this retrieval task.
Revised:  We then present a novel deep deformation-aware embedding to solve this retrieval task.
Edit intent: fluency
Original:  However, given a finite collection of 3D shapes, even the closest model to a query may not be a satisfactoryreconstruction .
Revised:  However, given a finite collection of 3D shapes, even the closest model to a query may not be satisfactory .
Edit intent: clarity
Original:  This gap between the deformed model and the query induces asymmetric relationships among the models, which cannot be dealt with typical metric learning techniques.
Revised:  This gap between the deformed model and the query induces asymmetric relationships among the models, which cannot be dealt with typical metric learning techniques.
Edit intent: fluency
Original:  This gap between the deformed model and the query induces asymmetric relationships among the models, which cannot be dealt with typical metric learning techniques.
Revised:  This gap between the deformed model and the query induces asymmetric relationships among the models, which cannot be handled by typical metric learning techniques.
Edit intent: fluency
Original: One hope of using non-elitism in evolutionary computation is that it aids leaving local optima.
Revised: One hope when using non-elitism in evolutionary computation is that it aids leaving local optima.
Edit intent: clarity
Original: One hope of using non-elitism in evolutionary computation is that it aids leaving local optima.
Revised: One hope of using non-elitism in evolutionary computation is that the ability to abandon the current-best solution aids leaving local optima.
Edit intent: clarity
Original:  Consequently, the ability of the (\mu,\lambda)  EA to leave local optima to inferior solutions does not lead to a runtime advantage.
Revised:  Consequently, the ability of the (\mu,\lambda) ~ EA to leave local optima to inferior solutions does not lead to a runtime advantage.
Edit intent: fluency
Original:  In a very sparse regime, our proposed method can handle graphs with five million nodes and tens of millions of edges in under ten minutes .
Revised:  In a very sparse regime, our proposed method can handle graphs with a million nodes and tens of millions of edges in under ten minutes .
Edit intent: clarity
Original:  In a very sparse regime, our proposed method can handle graphs with five million nodes and tens of millions of edges in under ten minutes .
Revised:  In a very sparse regime, our proposed method can handle graphs with five million nodes and tens of millions of edges .
Edit intent: clarity
Original: We study a setting where each agent in a network receives certain private signals generated by an unknown static statethat belongs to a finite set of hypotheses.
Revised: We consider the problem of distributed inference where agents in a network receives certain private signals generated by an unknown static statethat belongs to a finite set of hypotheses.
Edit intent: clarity
Original: We study a setting where each agent in a network receives certain private signals generated by an unknown static statethat belongs to a finite set of hypotheses.
Revised: We study a setting where each agent in a network observe a stream of private signals generated by an unknown static statethat belongs to a finite set of hypotheses.
Edit intent: clarity
Original:  To solve this problem in a communication-efficient manner, we propose an event-triggered distributed learning algorithm that is based on the principle of diffusing low beliefs on each false hypothesis.
Revised:  To solve this problem in a communication-efficient manner, we propose an event-triggered distributed learning rule that is based on the principle of diffusing low beliefs on each false hypothesis.
Edit intent: clarity
Original:  We formally characterize  stable and unstable domains for the stablecoin.
Revised:  We formally characterize stable and unstable for the stablecoin.
Edit intent: clarity
Original:  The unstable domain can be triggered by large deviations, collapsed expectations, and liquidity problems from deleveraging.
Revised:  The unstable domain can be triggered by large deviations, collapsed expectations, or liquidity problems from deleveraging.
Edit intent: fluency
Original:  We formally characterize a deflationary deleveraging spiral as a submartingale that can cause such liquidity problems in a crisis.
Revised:  We formally characterize a deflationary deleveraging spiral as a submartingale that can cause the system to behave in counterintuitive ways due to liquidity problems in a crisis.
Edit intent: clarity
Original:   We also demonstrate `perfect' stability results in idealized settings and discuss mechanisms which could bring realistic settings closer to the idealized stable settings.
Revised:  We also demonstrate `perfect' stability results in idealized settings and discuss mechanisms which could bring realistic settings closer to such idealized stable settings.
Edit intent: clarity
Original:  In this work we propose 1) to cast NAS as a problem of finding the optimal network generator and 2)  a new, hierarchical and graph-based search space capable of representing an extremely large variety of network types, yet only requiring few continuous hyper-parameters.
Revised:  In this work we 1) to cast NAS as a problem of finding the optimal network generator and 2) a new, hierarchical and graph-based search space capable of representing an extremely large variety of network types, yet only requiring few continuous hyper-parameters.
Edit intent: clarity
Original:  In this work we propose 1) to cast NAS as a problem of finding the optimal network generator and 2)  a new, hierarchical and graph-based search space capable of representing an extremely large variety of network types, yet only requiring few continuous hyper-parameters.
Revised:  In this work we propose 1) to cast NAS as a problem of finding the optimal network generator and 2) we propose a new, hierarchical and graph-based search space capable of representing an extremely large variety of network types, yet only requiring few continuous hyper-parameters.
Edit intent: fluency
Original:  We demonstrate the effectiveness of our strategy on six benchmark datasets and show that our search space generates extremely lightweight yet highly competitive models illustrating the benefits of a NAS approach that optimises over network generator selection .
Revised:  We demonstrate the effectiveness of this strategy on six benchmark datasets and show that our search space generates extremely lightweight yet highly competitive models illustrating the benefits of a NAS approach that optimises over network generator selection .
Edit intent: clarity
Original:  We demonstrate the effectiveness of our strategy on six benchmark datasets and show that our search space generates extremely lightweight yet highly competitive models illustrating the benefits of a NAS approach that optimises over network generator selection .
Revised:  We demonstrate the effectiveness of our strategy on six benchmark datasets and show that our search space generates extremely lightweight yet highly competitive models .
Edit intent: clarity
Original:  The convergence in law of the piecewise affine extension of the discrete process is also established.
Edit intent: coherence
Original: Lacking a drug or vaccine, our current strategy to contain the COVID-19 pandemic is by means of social distancing, specifically mobility restrictions and lock-downs.
Revised: Lacking a drug or vaccine, the current strategy to contain the COVID-19 pandemic is by means of social distancing, specifically mobility restrictions and lock-downs.
Edit intent: fluency
Original:  Under this regime, if an individual was exposed during their active week, by the time they complete their lock-down they willalready begin to exhibit symptoms.
Revised:  Under this regime, if an individual was exposed during their active week, by the time they complete their quarantine they will, in most cases, begin to exhibit symptoms.
Edit intent: clarity
Original:  Hence this strategy isolates the majority of exposed individuals during their asymptomatic phase.
Revised:  Hence this strategy isolates the majority of pre-symptomatic individuals during their asymptomatic phase.
Edit intent: clarity
Original: Lacking a drug or vaccine, the current strategy to contain the COVID-19 pandemic is by means of social distancing, specifically mobility restrictions and lock-downs.
Revised: Absent a drug or vaccine, the current strategy to contain the COVID-19 pandemic is by means of social distancing, specifically mobility restrictions and lock-downs.
Edit intent: fluency
Original: Lacking a drug or vaccine, the current strategy to contain the COVID-19 pandemic is by means of social distancing, specifically mobility restrictions and lock-downs.
Revised: Lacking a drug or vaccine, containing epidemic outbreaks is achieved by means of social distancing, specifically mobility restrictions and lock-downs.
Edit intent: clarity
Original:  How then do we isolate theseinvisible pre-symptomatic spreaders?
Revised:  How then do we isolate these pre-symptomatic spreaders?
Edit intent: clarity
Original:  Hence this strategy isolates the majority of pre-symptomatic individuals during their infectious phase, leading to a rapid decline in the viral spread - all while sustaining a continuously active economy at 50%DIFDELCMD < \\%%% %DIF < capacity .
Revised:  Hence this strategy isolates the majority of pre-symptomatic individuals during their infectious phase, leading to a rapid decline in the viral spread %DIFDELCMD < \\%%% %DIF < capacity .
Edit intent: clarity
Original: At the end of 2019 the world has seen the initial breakout of COVID-19, a disease caused by SARS-CoV2 virus in China.
Revised: At the end of 2019 the world has seen the initial outbreak of COVID-19, a disease caused by SARS-CoV2 virus in China.
Edit intent: fluency
Original:  As the disease spread globally, it becomes difficult to tract the transmission dynamics of this disease in all countries, as they may differ in geographical, demographical and strategical aspects.
Revised:  As the disease spread globally, it becomes difficult to tract the transmission dynamics of this disease in all countries, as they may differ in geographical, demographic and strategical aspects.
Edit intent: fluency
Original:  In this short note, the author proposes the utilization of a type of neural network to generate a global topological map for these dynamics, in which countries that share similar dynamics are mapped adjacently, and countries with significantly different dynamics are mapped far from each other.
Revised:  In this short note, the author proposes the utilization of a type of neural network to generate a global topological map for these dynamics, in which countries that share similar dynamics are mapped adjacently, while countries with significantly different dynamics are mapped far from each other.
Edit intent: coherence
Original:  Some initial experiments with with time series of patients numbers in more than 240 countries are explained in this not .
Revised:  Some initial experiments with with time series of patients numbers in more than 240 countries are explained in this note .
Edit intent: fluency
Original: A new mathematical model is proposed for quantitative description of the outbreak of novel coronavirus COVID-19 in China.
Revised: A mathematical model is proposed for quantitative description of the outbreak of novel coronavirus COVID-19 in China.
Edit intent: clarity
Original:  Since respiratory infections are one of the notable modern medical concerns and coughs being a common symptom of this, a system for recognizing and diagnosing infections based on raw cough data would have a multitude of beneficial research and medical applications.
Revised:  One of the notable modern medical concerns and coughs being a common symptom of this, a system for recognizing and diagnosing infections based on raw cough data would have a multitude of beneficial research and medical applications.
Edit intent: clarity
Original:  Since respiratory infections are one of the notable modern medical concerns and coughs being a common symptom of this, a system for recognizing and diagnosing infections based on raw cough data would have a multitude of beneficial research and medical applications.
Revised:  Since respiratory infections are one of the notable modern medical concerns that impose an immense worldwide health burden are respiratory infections. Since cough is an essential symptom of many respiratory infections, an automated system to screen for respiratory diseases based on raw cough data would have a multitude of beneficial research and medical applications.
Edit intent: clarity
Original:  In the literature, machine learning has  been successfully used to detect cough events in controlled environments.
Revised:  In literature, machine learning has been successfully used to detect cough events in controlled environments.
Edit intent: clarity
Original:  In the literature, machine learning has  been successfully used to detect cough events in controlled environments.
Revised:  In the literature, machine learning has already been successfully used to detect cough events in controlled environments.
Edit intent: coherence
Original:  In this work , we present a novel system that utilizes Convolutional Neural Networks (CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e., Bronchitis, Bronchiolitis, and Pertussis ) based on their unique cough audio features.
Revised:  In this paper , we present a novel system that utilizes Convolutional Neural Networks (CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e., Bronchitis, Bronchiolitis, and Pertussis ) based on their unique cough audio features.
Edit intent: clarity
Original:  In this work , we present a novel system that utilizes Convolutional Neural Networks (CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e., Bronchitis, Bronchiolitis, and Pertussis ) based on their unique cough audio features.
Revised:  In this work , we present a novel system that utilizes Convolutional Neural Networks (CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e., bronchitis, bronchiolitis and pertussis ) based on their unique cough audio features.
Edit intent: fluency
Original:  Our detection model achieves an accuracy of 90.17\% and a specificity of 89.73\%, whereas the diagnosis model achieves an accuracy of about 94.74\%and an F1 score of 93.73\%.
Revised:  Both proposed detection and diagnosis models achieve an accuracy of about 94.74\%and an F1 score of 93.73\%.
Edit intent: clarity
Original:  Moreover, our single diagnosis model is capable of distinguishing between different illnesses without the need of separate models.
Revised:  Moreover, the proposed single diagnosis model is capable of distinguishing between different illnesses without the need of separate models.
Edit intent: clarity
Original: Complex networks, such as transportation networks, social networks, or biological networks, translate the complex system they model often by representing  one type of interactions.
Revised: Complex networks, such as transportation networks, social networks, or biological networks, capture the complex system they model often by representing one type of interactions.
Edit intent: clarity
Original: Complex networks, such as transportation networks, social networks, or biological networks, translate the complex system they model often by representing  one type of interactions.
Revised: Complex networks, such as transportation networks, social networks, or biological networks, translate the complex system they model often by representing only one type of interactions.
Edit intent: clarity
Original:  In real world systems, there may be many aspects of the entities that connects them together.
Revised:  In real world systems, there may be many different aspects that connect entities together.
Edit intent: clarity
Original:  These can be captured using multilayer networks, which combine different modalities of interactions in one same model.
Revised:  These can be captured using multilayer networks, which combine different modalities of interactions in a single model.
Edit intent: clarity
Original:  Coupling in multilayer networks and multiplex networks may exhibit different properties , which can be related to the very nature of the data they model (or to events in time-dependant data).
Revised:  Coupling in multilayer networks may exhibit different properties , which can be related to the very nature of the data they model (or to events in time-dependant data).
Edit intent: coherence
Original:  Coupling in multilayer networks and multiplex networks may exhibit different properties , which can be related to the very nature of the data they model (or to events in time-dependant data).
Revised:  Coupling in multilayer networks and multiplex networks may exhibit different properties which can be related to the very nature of the data they model (or to events in time-dependant data).
Edit intent: fluency
Original:  We hypothesise that such properties may be reflected on the way layers are intertwined.
Revised:  We hypothesise that such properties may be reflected in the way layers are intertwined.
Edit intent: fluency
Original:  In this paper, we want to investigate these through the prism of layer entanglement in  multilayer networks.
Revised:  In this paper, we investigated these through the prism of layer entanglement in multilayer networks.
Edit intent: coherence
Original:  We test them on over 30 real-life networks in 6 different disciplines (social, genetic, transport, co-authorship, trade  and neuronal networks).
Revised:  We test over 30 real-life networks in 6 different disciplines (social, genetic, transport, co-authorship, trade and neuronal networks).
Edit intent: clarity