wanyu/IteraTeR_v2 huggingface dataset:
Original:  We assess the proposed method on synthetic and real automotive data, validating that our approach learns dynamic scenes - only by observing a video of this scene - and allows for rendering novel photo-realistic views of novel scene compositions with unseen sets of objects at unseen poses.
Revised:  We assess the proposed method on synthetic and real automotive data, validating that our approach learns dynamic scenes - only by observing a video of this scene -- and allows for rendering novel photo-realistic views of novel scene compositions with unseen sets of objects at unseen poses.
Edit intent: fluency
Original:  In the experiments, we illustrate the proposed methods on several problems and provide observations on their run time , which are comparable with the state-of-the-art .
Revised:  In the experiments, we illustrate the proposed methods on several problems and provide observations on their run time .
Edit intent: clarity
Original:  We develop a version of the celebrated Page's CUSUM test, specifically tailored to pandemic data.
Revised:  The focus of the work is to develop a version of the celebrated Page's CUSUM test, specifically tailored to pandemic data.
Edit intent: clarity
Original:  Its application to the publicly-available sequence of new positive individuals per day , from different countries , is detailed in 1 .
Revised:  Its application to the publicly-available sequence of new positive individuals per day from different countries , is detailed in 1 .
Edit intent: fluency
Original:  Its application to the publicly-available sequence of new positive individuals per day , from different countries , is detailed in 1 .
Revised:  Its application to the publicly-available sequence of new positive individuals per day , from different countries 1 .
Edit intent: clarity
Original:  Our approach deviates significantly from most methods of the literature as it relies on a principle that can be applied in many different ways, for any problem, network or pruning structure.
Revised:  Our theoretically-grounded approach is versatile and can be applied in many different ways, for any problem, network or pruning structure.
Edit intent: clarity
Original:  Our approach deviates significantly from most methods of the literature as it relies on a principle that can be applied in many different ways, for any problem, network or pruning structure.
Revised:  Our approach deviates significantly from most methods of the literature as it relies on a principle that can be applied to any problem, network or pruning structure.
Edit intent: clarity
Original:  Yet, the severe perturbation caused by most pruning approaches is thought to hinder their efficacy . Drawing inspiration from Lagrangian Smoothing, we introduce a new technique, Selective Weight Decay (SWD), which achieves continuous pruning throughout training.
Revised:  Yet, the severe perturbation caused by most pruning approaches is thought to hinder their efficacy . Drawing inspiration from Lagrangian Smoothing, we introduce a new technique, Selective Weight Decay (SWD), which realizes efficient continuous pruning throughout training.
Edit intent: clarity
Original:  Our theoretically-grounded approach is versatile and can be applied to any problem, network or pruning structure .
Revised:  Our theoretically-grounded approach is versatile and can be applied to multiple tasks, networks and pruning structures .
Edit intent: clarity
Original:  On the ImageNet ILSVRC2012 dataset with unstructured pruning and the same target rate of 2.5\%, SWD attains 84.6\% Top-5 accuracy instead of the 77.07\% reached by the reference .
Revised:  On the ImageNet ILSVRC2012 datasets .
Edit intent: coherence
Original: We present a new training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to benefit from longer audio streams as input, while only requiring partial transcriptions of such streams during training.
Revised: We present a training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to benefit from longer audio streams as input, while only requiring partial transcriptions of such streams during training.
Edit intent: clarity
Original: We present a new training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to benefit from longer audio streams as input, while only requiring partial transcriptions of such streams during training.
Revised: We present a new training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to learn to exploit context audio from a stream, using segmented or partially labeled sequences of the stream during training.
Edit intent: clarity
Original:  We show that this extension of the acoustic context during training and inference can lead to word error rate reductions of more than 6\% in a realistic production setting  .
Revised:  We show that the use of context audio during training and inference can lead to word error rate reductions of more than 6\% in a realistic production setting .
Edit intent: clarity
Original:  We show that this extension of the acoustic context during training and inference can lead to word error rate reductions of more than 6\% in a realistic production setting  .
Revised:  We show that this extension of the acoustic context during training and inference can lead to word error rate reductions of more than 6\% in a realistic production setting for a voice assistant ASR system .
Edit intent: clarity
Original:  Finally, we visualize RNN-T loss gradients with respect to the input features in order to illustrate the ability of a long short-term memory (LSTM) based ASR encoder to exploit long-term context  .
Revised:  To gain further insight into the ability of a long short-term memory (LSTM) based ASR encoder to exploit long-term context .
Edit intent: clarity
Original:  Despite the best practices employed in design and manufacturing of modern MCS devices, complexity and modular nature of these systems often introduces internal steps and crevices in the flow path which can serve as nidus for thrombus formation.
Revised:  Despite the best practices employed in design and manufacturing of modern ventricular assist devices, complexity and modular nature of these systems often introduces internal steps and crevices in the flow path which can serve as nidus for thrombus formation.
Edit intent: clarity
Original:  The results offer guidance for design and operation of blood-contacting devices.
Revised:  The results offer insights for design and operation of blood-contacting devices.
Edit intent: clarity
Original:  While mechanics compartment models are widely-used in epidemic modeling, data-driven models are emerging for disease forecasting.
Revised:  While mechanics compartment models are widely used in epidemic modeling, data-driven models are emerging for disease forecasting.
Edit intent: fluency
Original:  As a case study, we compare these two types of models for COVID-19 forecasting and notice that physics-based  models significantly outperform deep learning models.
Revised:  As a case study, we compare these two types of models for COVID-19 forecasting , we notice that physics-based models significantly outperform deep learning models.
Edit intent: coherence
Original:  To understand the inferior performance of deep learning, we investigate the generalization problem in forecasting.
Revised:  Such performance differences highlight the generalization problem in forecasting.
Edit intent: clarity
Original:  This calls attention to rethink generalization especially for learning dynamical systems.
Revised:  This calls attention to rethink generalization for learning dynamical systems.
Edit intent: clarity
Original: The thermodynamic binding networks (TBN) model was recently developed as a tool for studying engineered molecular systems.
Revised: The thermodynamic binding networks (TBN) model is a tool for studying engineered molecular systems.
Edit intent: clarity
Original:  We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy : those that maximize the number of bonds and complexes ) . We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Revised:  We formulate as an integer program the NP-hard problem of computing stable (a.k.a., minimum energy : those that maximize the number of bonds and complexes ) . We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Edit intent: clarity
Original:  We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy : those that maximize the number of bonds and complexes ) . We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Revised:  We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy : those that maximize the number of bonds and complexes . We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Edit intent: fluency
Original:  We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy : those that maximize the number of bonds and complexes ) . We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Revised:  We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy : those that maximize the number of bonds and complexes ) . We provide open-source software solving this integer program. We give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers.
Edit intent: clarity
Original:  Finally, we show that the TBN 's Graver basis (a kind of certificate of optimality in integer programming) has a natural interpretation as the "fundamental components" out of which locally minimal energy configurations are composed.
Revised:  Finally, we show that the TBN has a natural interpretation as the "fundamental components" out of which locally minimal energy configurations are composed.
Edit intent: coherence
Original: In this paper, we provide exponential rates of convergence to the Nash equilibrium of continuous-time  game dynamics such as mirror descent (MD) and actor-critic (AC)  in N-player continuous  games that are either potential games or monotone games but possibly potential-free.
Revised: In this paper, we provide exponential rates of convergence to the Nash equilibrium for continuous-time game dynamics such as mirror descent (MD) and actor-critic (AC) in N-player continuous games that are either potential games or monotone games but possibly potential-free.
Edit intent: clarity
Original: In this paper, we provide exponential rates of convergence to the Nash equilibrium of continuous-time  game dynamics such as mirror descent (MD) and actor-critic (AC)  in N-player continuous  games that are either potential games or monotone games but possibly potential-free.
Revised: In this paper, we provide exponential rates of convergence to the Nash equilibrium of continuous-time game dynamics such as mirror descent (MD) and actor-critic (AC) . We perform our analysis in N-player continuous games that are either potential games or monotone games but possibly potential-free.
Edit intent: clarity
Original:  In the second part of this paper, using relative concavity, we provide a novel relative characterization of monotone games and show that MD and its discounted version converge with O(e^{-\beta t}) in relatively strongly and relatively hypo-monotone games .
Revised:  In the second part of this paper, we specialize our results to games that admit a relatively strongly concave potential and show that MD and its discounted version converge with O(e^{-\beta t}) in relatively strongly and relatively hypo-monotone games .
Edit intent: clarity
Original:  Moreover, these rates extend their known convergence conditions and also improve the results in the potential game setup . Simulations are performed which empirically back up our results.
Revised:  Moreover, these rates extend their known convergence conditions . Simulations are performed which empirically back up our results.
Edit intent: coherence
Original:  In order to ensure the 2nd-pass completes quickly, we explore non-causal Conformer layers that feed into the same 1st-pass RNN-T decoder, an algorithm we called Cascaded Encoders  .
Revised:  In order to ensure the 2nd-pass completes quickly, we explore non-causal Conformer layers that feed into the same 1st-pass RNN-T decoder, an algorithm called Cascaded Encoders .
Edit intent: fluency
Original:  This is  natural prerequisite for practical identifiability.
Revised:  This is a natural prerequisite for practical identifiability.
Edit intent: fluency
Original:  As another related application of model theory in this area, we construct a nonlinear ODE system with one output such that single-experiment and mutiple-experiment identifiability are different for the system.
Revised:  As another related application of model theory in this area, we construct a nonlinear ODE system with one output such that single-experiment and multiple-experiment identifiability are different for the system.
Edit intent: fluency
Original: Neuronal dynamics is driven by externally imposed or internally generated random excitations/noise, and is often described by systems of  stochastic ordinary differential equations.
Revised: Neuronal dynamics is driven by externally imposed or internally generated random excitations/noise, and is often described by systems of random or stochastic ordinary differential equations.
Edit intent: clarity
Original:  A solution to these equations is the joint probability density function (PDF) of neuron states.
Revised:  A solution to these equations is the joint probability density function (PDF) of system states.
Edit intent: clarity
Original:  The closures are tested for stochastic leaky integrate-and-fire (LIF) and FitzHugh-Nagumo (FHN) neurons driven by sine-Wiener noise.
Revised:  The closures are tested for stochastic leaky integrate-and-fire and FitzHugh-Nagumo (FHN) neurons driven by sine-Wiener noise.
Edit intent: clarity
Original: We consider planar tiling and packing problems with polyomino pieces and a polyomino container P. A polyomino is a polygonal region with axis parallel edges and corners of integral coordinates, which may have holes.
Revised:  A polyomino is a polygonal region with axis parallel edges and corners of integral coordinates, which may have holes.
Edit intent: coherence
Original:   We give two polynomial time algorithms, one for deciding if P can be tiled with 2\times 2 squares (that is, deciding if P is the union of a set of non-overlapping copies of the 2\times 2 square ) and one for packing P with a maximum number of non-overlapping and axis-parallel 2\times 1 dominos, allowing rotations of 90^\circ.
Revised:  We give two polynomial time algorithms, one for deciding if P can be tiled with 2\times 2 squares (that is, deciding if P is the union of a set of non-overlapping k\times k squares ) and one for packing P with a maximum number of non-overlapping and axis-parallel 2\times 1 dominos, allowing rotations of 90^\circ.
Edit intent: clarity
Original:   We give two polynomial time algorithms, one for deciding if P can be tiled with 2\times 2 squares (that is, deciding if P is the union of a set of non-overlapping copies of the 2\times 2 square ) and one for packing P with a maximum number of non-overlapping and axis-parallel 2\times 1 dominos, allowing rotations of 90^\circ.
Revised:  We give two polynomial time algorithms, one for deciding if P can be tiled with 2\times 2 squares (that is, deciding if P is the union of a set of non-overlapping copies of the 2\times 2 square ) and one for packing P with a maximum number of non-overlapping and axis-parallel 2\times 1 dominos, allowing rotations by 90^\circ.
Edit intent: clarity
Original:  These are classical problems with important applications in VLSI design, and the related problem of finding a maximum packing of 2\times 2 squares is known to be NP-Hard [J. ~ Algorithms 1990].
Revised:  These are classical problems with important applications in VLSI design, and the related problem of finding a maximum packing of 2\times 2 squares is known to be NP-Hard [J. Algorithms 1990].
Edit intent: fluency
Original:  For our three problems there are known pseudo-polynomial time algorithms, that is, algorithms with running times polynomial in the area of P.
Revised:  For our three problems there are known pseudo-polynomial time algorithms, that is, algorithms with running times polynomial in the area of P.
Edit intent: fluency
Original:  Although this approach was considered for the Helmholtz equation before, our new insights show that some of its important properties have remained hidden.
Revised:  Altough this approach was considered for the Helmholtz equation before, our new insights show that some of its important properties have remained hidden.
Edit intent: fluency
Original: Real data often appear in the form of multiple incomplete views , and incomplete multi-view clustering is an effective method to integrate these incomplete views.
Revised: Real data often appear in the form of multiple incomplete views . Incomplete multi-view clustering is an effective method to integrate these incomplete views.
Edit intent: coherence
Original:  To overcome this limitation, we propose a novel View Variation and View Heredity approach ( V 3 H ).
Revised:  To overcome this limitation, we propose a novel View Variation and View Heredity approach ( V3H ).
Edit intent: fluency
Original:  Inspired by the variation and the heredity in genetics, V 3 H first decomposes each subspace into a variation matrix for the corresponding view and a heredity matrix for all the views to represent the unique information and the consistent information respectively.
Revised:  Inspired by the variation and the heredity in genetics, V3H first decomposes each subspace into a variation matrix for the corresponding view and a heredity matrix for all the views to represent the unique information and the consistent information respectively.
Edit intent: fluency
Original:  Their parameters are the local fields, which describe site-specific patterns of amino-acid conservation, and the two-site couplings, which mirror the coevolution between pairs of distinct sites.
Revised:  Their parameters are the local fields, which describe site-specific patterns of amino-acid conservation, and the two-site couplings, which mirror the coevolution between pairs of sites.
Edit intent: clarity
Original:  This coevolution reflects structural and functional constraints acting on protein sequences during evolution , and couplings can a priori connect any pairs of sites, even those being distant along the protein chain, or distant in the three-dimensional protein fold .
Revised:  This coevolution reflects structural and functional constraints acting on protein sequences during evolution .
Edit intent: clarity
Original:  The most conservative choice to describe all of the coevolution signal is to include all possible two-site couplings into the PM.
Revised:  The most conservative choice to describe the coevolution signal is to include all possible two-site couplings into the PM.
Edit intent: clarity
Original:  In this work, we introduce a  parameter-reduction procedure via iterative decimation of the less statistically significant couplings .
Revised:  In this work, we introduce a general parameter-reduction procedure via iterative decimation of the less statistically significant couplings .
Edit intent: clarity
Original:  We propose an information-based criterion that identifies couplings that are either weak , or statistically unsupported .
Revised:  We propose an information-based criterion that selects either weak or statistically unsupported .
Edit intent: clarity
Original:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Revised:  We show that our procedure allows one to remove more than 90 \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Edit intent: fluency
Original:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Revised:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM , and the resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Edit intent: coherence
Original:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Revised:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, hence more robust to noise , and its couplings are more easily interpretable .
Edit intent: coherence
Original:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise , and its couplings are more easily interpretable .
Revised:  We show that our procedure allows one to remove more than 90 \% of the PM couplings, while preserving the predictive \\%DIF > of the PM couplings, while preserving the predictive and generative properties of the original dense PM . The resulting model is far away from criticality, meaning that it is more robust to noise .
Edit intent: coherence