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Methods, materials and validation are of a sufficient quality ['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
Following the authors logic, normal large batch training decrease the variability of <H>_k and which converges to flat minima. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
If you want your work applied in clinics, this is much more important than improving the results ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Are the results on the entire parametric maps in line with the current results ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
This is not true in a beta-VAE ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
First, it is not fully clear where this number 3 comes from , and second, the quality of the work speaks for itself ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'non', 'non', 'non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
It is not clear if the values for the existing methods in Table 2 correspond to the winning teams of the IDRID challenge ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
"For instance, the claim of ""stronger cue-specific differences across the cue stimulus window"" between fast and slow intrinsic timescale neurons in the RNN model isn't clearly supported by the heatmap in Figure 3 -- the cue-specific differences for the short instrinsic timescale group to me appears to be at least as great as that of the long intrinsic timescale group within the cue stimulus window" ['non', 'non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
The structure of the paper is strange because it discusses attribution priors but then they are not used for the method ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Pros - The performance of the proposed method is better than the existing multi-objective architecture search methods in the object classification task ['non', 'non', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
The task itself would imply that a deep network classifier is potentially an overkill. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
This sheds new light on how artificial network algorithms might be implementable by the brain ['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
The writers have put their contributions in context well and the presentation of the paper itself is very clear ['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
In contrast, ACNN auto-encoders train their encoder and decoder in conjunction. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
In particular, it learns the embedding of paired nodes simultaneously for multiple times, and use the mean values as the final representation. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
This paper is well-written ['pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
I believe a more measured conclusion (perhaps that we *need* more regularization methods, but even then we may not be able to get perfect robustness and accuracy) would better fit the strong results presented in the paper ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
In the other case, the Bayes-optimal classifier is robust, but neural networks fail to learn the robust decision boundary. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
"I would recommend weakening or at least toning down certain ""marketing"" claims like ""3 times finer than the highest resolution ever investigated in the domain of voxel-based shape generation"", or ""the finest resolution ever achieved among voxel-based models in computer graphics""." ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Assessing in-focus will even get rid of blurred frames and frames as discussed in the Appendix. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
BTW, in the Section 4.3, what does [-1, 1]^2 mean ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
However, the multiple grandiose statements, and some that are downright misleading left me puzzling what I learned ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Their statement of the novelty of their method: (1) allowing each feature to have its own transformation was not clear ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
It is unclear how the model actually operates and uses attention during execution ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Regardless, trying to paint others work negatively by arguments to some general issue with established performance metrics is disingenuous ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Given its technical details it was reasonably straightforward to follow ['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
No effort has been made to fuse the proposed pipeline into a medical-image analysis specific methodological contribution ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
But this looks wrong since it should include the distribution of all instances of 3D-BPP. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
"Largely contradicts this one ""It is probable that revolutionary computational systems can be created in this way with only moderate expenditure of resources and effort"" I felt the paper could have done more to link with current state-of-the-art AI approaches" ['con', 'con', 'con', 'con', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Was the setup the same as in Gessert et al (2019), i.e. with a robot moving the object and mirrors moving the OCT FOV? ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
I believe the experiments are thorough and well designed to back the claims of the paper ['non', 'non', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
The proposed method is very similar with the unsupervised GraphSAGE , which also optimizes Eq.(7). ['con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Other comments: It is assumed that the noise of value and policy network is zero at the leaf node. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Experimental results show that the proposed algorithm outperform the MCTS algorithms ['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
Whereas, if internal matrices have a number of dimensions lower than the rank of the original matrix, these matrices act as filters on features or feature combination. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Now, it is difficult to connect use of prior and improvement in ECE. ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
I think more examples, such as in section 8.1, should be put in the main text ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Minor point: - The extension of the method to Marked Temporal Point Processes in the Evaluation section seems out of place, esp. ['non', 'non', 'non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Hence, without non-linear functions, where is the added value of the method ['non', 'non', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con', 'con'] paper quality
Thus I think this method is itself interesting ['non', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro'] paper quality
Criterion 2 (b) is not clear ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Clarity: I found the paper to be very well written with a clear exposition of the material and sound development of the technical details ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
In the main text, no results are presented that warrant such a conclusion ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
There can be more discussion here.The authors propose a framework to utilize one model under different acquisition context scenarios. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Why is it worthwhile to study this task separately ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Some points to address are listed in the following: The early stopping is not clear ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Also, it would be very interesting to use these models to predict situations that might trigger maladaptive behaviors, by finding scenarios in which the pathological behavior becomes optimal. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
So, even if those results do not preclude the use of sophisticated DRL techniques for solving geometric knapsack problems, it would be legitimate to empirically compare these techniques with the polytime asymptotic approximation algorithms already found in the literature. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
For FA networks, it's unclear why an attacker could not access true gradient, and be forced to use the approximate gradient ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
I would suggest to include the F1-score and the area under the Precision/Recall curve, instead , which have been used already in other studies (see [1] and [2], for example, or Orlando et al. 2017 in the submitted draft). ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The reason for high performance of the proposed method can be explained with the required number of parameters to train the method. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The novelty of the proposed framework is to take the label structure into account and to learn label dependencies, based on the idea of conditional learning in (Chen et al., 2019) and the lung disease hierarchy of the CheXpert dataset (Irvin and al., 2019). ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
This paper presents an emprical study of how a properly tuned implementation of a model-free RL method can achieve data-efficiency similar to a state-of-the-art model-based method for the Atari domain. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
2- It is not clear why the histology images were used for denoising network training ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The formalization that the authors proposed is basically the definition of curriculum learning ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Additionally, it is well known that Option-Critic approaches (when unregularized) tend to learn options that terminate every step [2]. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Other specific suggestions: Section 2: region of interest (ROI) performing motions does not make sense to me ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The authors had better compare segmentation result between CTP with orginal MRI and CTP with CGAN MRI ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
5- How is the complex component of the signal concatenated into a channel ? ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non'] paper quality
The experiments are not strong ['arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Its an opinion piece. ['non', 'non', 'non', 'non', 'non'] paper quality
This idea is simple and works well ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The authors should have identified a task where networks trained on MNIST perform poorly, and then propose a different strategy or architecture ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
It would be interesting to simulate such an experiment by taking an additional data set with vessel annotations (e.g., some of those that I suggested before, HRF, CHASEDB1 or DR HAGIS) and evaluate the performance there, without using any of their images for training ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The improvement gained by the proposed method validates the effectiveness of recurrent units, and the most significant gain is from the false positive rates. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The study has potential and could have interesting applications in clinical settings ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
How does this parameter affect the performance ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Namely, the framework is based on the actor-critic paradigm, and uses a conditional query learning model for performing composite actions (selections, rotations) in geometric bin packing. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Did you train on some other dataset and test on skin lesion dataset ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
It does not give the explicit relations of the sample complexity with respect to different quantities in the algorithms ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The presented paper aims to label and remove irrelevant sequences from laparoscopic videos. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Transfer learning and dealing with small datasets is an important area of research - The paper proposes a novel method, enabling pretraining on several different tasks instead of only one dataset (e.g. ImageNet) like done most of the times - Results show clear performance increase on small datasets - Proper experiment setup and validation - Clearly written and comprehensible - Code is openly available - Little comparison to other state-of-the-art methods for transfer learning ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
If this is the case, I feel like the empirical results are not novel enough to create value for the community and too tied to a particular approach to hierarchy which does not align with much of the past work on HRL ['non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
7- What is the number of parameters required for each method in Table 1? ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non'] paper quality
Although innovative and promising , the work is quite preliminary and would benefit from comparison and validation with real human behavior ['non', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
5- Obtaining quantitative comparison results for staining accuracy is not feasible due to the reasons clearly defined by the authors ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
I am advocating open data access and reproducible research. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The proposed method is very simple ['arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
"The authors mention that Feudal approaches ""employ different rewards for different levels of the hierarchy rather than optimizing a single objective for the entire model as we do.""" ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
Weaknesses: - The experiments are done on CIFAR-10, CIFAR-100 and subsets of CIFAR-100. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
It is difficult to judge whether the new model is important because it has not been evaluated except by eye it does seem to reconstruct an image ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The paper is written clearly ['arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Prior work: the paper seems to ignore a plethora of prior work around studying adversarial robustness and understanding its roots ['non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
STRENGTHS + Decoupling instruction-to-action mapping by introducing goals as a learned intermediate representation has advantages, particularly for goal-directed instructions ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Clear presentation of thorough work, exploring an important question ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Is there a reason for not using it? ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
pseudo-url] yet the presented method is benchmarked only against 3 ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
In general this list is not comprehensive either: there are many relevant connections to the robustness-accuracy tradeoff (pseudo-url, pseudo-url), and other works. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
The paper lacks insight about a principled way to label such examples, the costs associated with such labeling, and impacts of the labeling quality on accuracy ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Instead, you should have made the comparison and highlighted the differences clearly ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
4- How does the specifics of the network architecture influence the performance ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
To me the proposed approach does not seem particularly novel and the idea that hierarchy can be useful for multi-task learning is also not new ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The work is lacking a discussion of the most recent work in the similarity of visual processing in convnets to brain data, which incorporate recurrence into convnets (Nayebi et al. 2018, Kubilius et al. 2018 and 2019), thereby potentially allowing for similar behavior as a PredNet. ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
"Minor Example 2: ""A"" -> ""AI""" ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
The area under the ROC curve is not a proper metric for evaluating a vessel segmentation algorithm due to the class imbalance between the TP and TN classes (vessels vs. background ratio is around 12% in fundus pictures) ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
For instance, how is the b at line 63 related to the activation x_i and ReLU at lines 75 and 76? ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality
However, I feel that the work lacked clarity when it came to interpretation of the results ['non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Because of that, the experimental evaluation remains vague as well, as the criteria are tested on one data set by visual inspection ['non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
My main concern here, besides the motivations that I did not fully understand (s.b. ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality
Those three papers should be included in the state-of-the-art section : - Constrained convolutional neural networks for weakly supervised segmentation, Pathak et al., ICCV 2015 - DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks, Rajchl et al., TMI, 2016 - Constrained-CNN losses for weakly supervised segmentation, Kervadec et al., MIDL 2018 Since the AJI and object-level Dice are not standard and introduced in other papers, it would be easier to put their formulation back in the paper, so the reader does not have to go look for it. ['non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality