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Indeed the critical factor is not to capture the instrument's appearance but rather model how variable the anatomical environment is. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Detailed: Page 3, last paragraph: Why did you not use bias terms in your model? ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Perhaps PCD-1 results in performance that is far better than AdVIL ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Moreover, they have done some ablation studies to show the importance of the receptive field and temporal frames for MRF reconstruction. ['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, that still makes a 10% prediction error quite high in my book, and worthy of contextualization. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
This will provide more insights or explanations. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Although the concept of normalizing flow is simple, and it has been applied to other models such as VAE , there seems no work on applying it for policy optimization ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', ... |
The criteria remain very vague and seem be to applicable mainly to the evaluated data set (e.g. what defines a steep decrease?). ['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 qu... |
There will be domain shift problems for the simple methods but same is true for the presented method. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
This is a very interesting task and the dataset/models are a very useful contribution to the community ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The paper reads well and the methodology seems to be interesting ['arg', 'arg', 'arg', 'arg', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The contribution is minor, and the reasoning behind it could be better motivated ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. ['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 results suggest that participants perform better with the system. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Repeat this process recursively tens to trillions of times, and suddenly you have a brain controlling a body in the world or doing something else equally clever. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'no... |
Is there some reference for multiplicative residual connections ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The main weakness of the paper is in the methods section ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The authors need to give more discussion and explanation about it ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Independent and identically distributed? ['non', 'non', 'non', 'non', 'non'] paper quality |
Page 4, Monotony. ['non', 'non', 'non', 'non', 'non'] paper quality |
The leader is modeled as a semi-MDP with event-based policy gradients and modules to model/predict followers' actions. ['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 |
In fact, the model presented in the paper has a major obscure point ['non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The hyper-parameters of autoencoder and the recon decoder should be more clearly stated for reproducibility ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Are they free-form instructions ['arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The only way training size can influence AUC is by influencing the training of the model. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Authors compare their approach with COMA (discrete actions and counterfactual (semi-centralized) baseline) and MADDPG (also uses centralized value function and continuous actions) MAAC is evaluated on two 2d cooperative environments, Treasure Collection and Rover Tower. ['non', 'non', 'non', 'non', 'non', 'non', 'non',... |
Multi-task learning can extract a shared representation that is generalisable and this is evidenced in the results in the TUPAC16 set. ['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 |
As I understand it, real improvements in predicting clinical variables has not been shown to be reproducible so this would be a significant claim of this paper ['non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'... |
AMOUNT OF ERROR Throughout the paper, prediction errors (additive) up to 10% are described as small, and that is surprising (5% in Exp 1, 10% in Exp 2, 7% in Exp 3, 10% in Exp 4). ['non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg',... |
The largest batch considered is 64*32, which is relatively small ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The paper defines r as ratio of network updates to environment interactions to describe model-free and model-based methods, and hypothesizes that model-based methods are more data-efficient because of a higher ratio r. To test this hypothesis, the authors take Rainbow DQN (model-free) and modify it to increase its rati... |
The methods section lacks details for reproducing the work ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
This paper discusses State Representation Learning for RL from camera images. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
"For example ... ""A neuron simply sits and listens." ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
The paper initially states that this distance function is computed from learned embeddings of human demonstrations, however these are presumably instructions rather than demonstrations ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', '... |
How would this affect the results? ['non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
To achieve this , the idea of introducing Dirichlet distribution after neural network is used from Evidential Deep Learning (EDL) paper. ['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 |
Another, relatively small point which the authors glance over is the matter of efficient training ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
This will potentially bring us closer to rapid evaluation of lesions during surgical operation using fast CM ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The experimental results are carried out under the very simplified settings for both the proposed algorithm and the baseline MCTS ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
BLAMING AGE Honestly, I found it quite a weak argument to put the lack of generalization of the approach on age (p. 10 ). ['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', 'non', 'non'] paper qu... |
The experimental result demonstrates some improvement over existing methods. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
The results for vessel segmentation in IDRID images do not look as accurate as those in the DRIVE data set ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
"After the publication at MICCAI 2019 of the work ""Distribution Matching Losses Can Hallucinate Features in Medical Image Translation"" and similar other works, it has started becoming apparent that the simple visual similarity between samples generated by a GAN and true samples from a specific distribution doesn't en... |
Please modify the paper to make this clear. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Then, in Figure 2, human normalized scores are reported for varying amounts of experience for the variants of Rainbow, and compared against SiMPLe with 100k interactions, with the claim that the authors couldn't run the method for longer experiences. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'... |
is the lack of measurable criteria ['arg', 'arg', 'arg', 'arg', 'arg', 'arg'] 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 |
Experimental results demonstrate that the proposed method can achieve better performance than non-ensemble one under the same training steps, and the decision space can also be stabilized. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non... |
Why is it worthwhile to study this task separately ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The trained network is then fine tuned with a direct CRF loss, as in Tang et al. Evaluation is performed on two datasets in several configurations (with and without CRF loss, and variation on the labels used) ; showing the effects of the different parts of the method. ['non', 'non', 'non', 'non', 'non', 'non', 'non', '... |
You might be able to convince me more if you had a stronger baseline e.g. a bag-of-words Drawer model which works off of the average of the word embeddings in a scripted Teller input ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'ar... |
A novel dynamic weight prediction model is proposed to learn to predict the kernel weights for each convolution based on different context settings. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] pa... |
Some minor issues: Figure 2 is not referenced anywhere in the main text ['non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
It is quite well known that more training data, in general, results in improved performance of networks. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
In particular, the setting of synaptic decay constants is an important detail in a paper about working memory. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
The work has promising implications for computational psychiatry , but probably not for RL at this point ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
While completely alleviating this concern may once again be quite difficult/impossible , it could be significantly alleviated by generating training samples dynamically (at every iteration) instead of generating a dataset in one shot and training on it ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'no... |
What precisely about predictive coding makes the similarity to brain data expected ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Equation (1) and (2) are extremely clear ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
One needs to go see Appendix C to understand what the model used (SQL) consists in ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The technical aspects of the paper seem correct , though I have some higher-level conceptual concerns ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Also, do the CNN layers correspond to cell populations , and if so, why is it reasonable to collapse the time dimension after the first layer ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'a... |
CNN vs Linear SVM: I am confused about why we would expect a CNN to be able to learn the Bayes-optimal decision boundary but not the Linear SVM ['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', ... |
The authors consider how biologically motivated synaptic eligibility traces can be used for backpropagation-like learning, in particular by approximating local gradient computations in recurrent neural networks. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'n... |
The construction of the dataset focuses on demonstrating that compositional action classification and long-term temporal reasoning for action understanding and localization in videos are largely unsolved problems, and that frame aggregation-based methods on real video data in prior work datasets, have found relative su... |
For example, normalizing flows are defined in Section 4, and then it is directly claimed that normalizing flows can be applied to policy optimization, without giving details on how it is actually applied, e.g., what is the objective function ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', ... |
Our challenge is to understand how this occurs. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Either way this is important work, with many interesting future directions ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
"It would be interesting to know that aspect, as it is crucial to allow the network to learn to ""transfer"" its own ability for detecting a new region from one data set to another." ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'no... |
I believe the concept of using predictive coding and unlabeled video data to train convnets is a great idea ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Most of the experiments revolve around existing attribution prior methods ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
It is difficult for me to accept it ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
And it seems to have very relevant connections to your work. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
As this direction (of increased resolution to make the problem less artificial) is likely to be important, a brief discussion of this finding from the main paper text would be appropriate - p3 resiliance -> resilience - p4 objects is moved -> object is moved - p6 actions itself -> actions themselves; builds upon -> bui... |
Experiments show that the proposed method outperforms the model trained on the context-agnostic setting and acquires similar results to models trained by context-specific settings.1). ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'n... |
The introduction and description of the state of the art, in addition to the main limitations of popular algorithms is very clear and interesting to read ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg... |
Overall, the idea is presented clearly and the writing is well structured ['non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
4- The authors conclude that the despeckling NN is crucial to obtain realistic images, however, the results presented in Figures 8 and 9 do not provide enough information to support this conclusion ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'a... |
It seems that the DWP need to generate a specific weight each time. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
For example: Is there any difference between the results of table 1, if we look at the cooperative setup ['non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The results of the model was compared also to the state of the art.From the following sentence, I understand that for each pathology, a different model was trained. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', ... |
The paper is written as if the conclusions could be extended to model-based methods in general. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Mostly neuroscientific, but addresses the important topic of how models from machine learning can best be used in neuro research ['non', 'non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
The authors combine DL and computer vision methods to digitally stain confocal microscopy images to generate H&E like images. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
"It is not clear if the paper is presenting ""expected gradients"" or existing attribution priors" ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
In fact, if real-world datasets end up being like the asymmetric dataset, then the results of this paper would actually indicate the *opposite* of the above statement ['non', 'non', 'non', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'... |
Section 3: combing should be combining ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
Have you tried baselines like these? ['non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
8-The lack of scalability and the requirement of computational time is highlighted in the introduction and abstract. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] 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', ... |
Section 3.3 is confusing to me ['arg', 'arg', 'arg', 'arg', 'arg', 'arg'] paper quality |
However, authors use Jaccard coef. ['non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Quantitative assessment is fairly limited, and yielding underwhelming results compared to individual networks (ex. CycleGAN). ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
Perhaps compare to reference models [11] or [10] rather than a 'vanilla' RNN , as this amounts to not using any prior information about the task (which, by construction, we 'know' is useful) ['arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'arg', 'a... |
Instead of learning the conditional intensity for the point process, as is usually the case, the authors instead propose an elegant method based on Normalizing Flows to directly learn the probability distribution of the next time step ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', ... |
Summary: Authors present AnatomyGen, a CNN-based approach for mapping from low-dimensional anatomical landmark coordinates to a dense voxel representation and back, via separately trained decoder and encoder networks. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'no... |
The authors claim the formalization of the problem to be one of their contributions. ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
References Vogel & Jurafsky (2010). ['non', 'non', 'non', 'non', 'non', 'non', 'non', 'non'] paper quality |
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