Questions tagged [papers]

For questions related to artificial intelligence research papers. So, you should use this tag if you want someone to clarify something in a research paper.

Filter by
Sorted by
Tagged with
0
votes
0answers
21 views
+50

In this paper, how does scaling the filter instead of the image generate saliency maps of the same size and resolution as the input image?

In this paper, in section 3.1, the authors state Scaling the filter instead of the image allows the generation of saliency maps of the same size and resolution as the input image. How is this ...
2
votes
2answers
84 views

In layman terms, what does "attention" do in a transformer?

I heard from many people about the paper titled Attention Is All You Need by Ashish Vaswani et al. What actually does the "attention" do in simple terms? Is it a function, property, or some ...
0
votes
0answers
33 views
+50

Understanding gumbel-softmax backpropagation in Wav2Vec papers

I'm studying the series of Wav2Vec papers, in particular, the vq-wav2vec and wav2vec 2.0, and have a problem understanding some details about the quantization procedure. The broader context is this: ...
0
votes
0answers
24 views

Bert vs Sentence-Bert

I read a paper about Rumor detection and they used BERT as an unsupervised language representation, fine-tuning it using a small dataset, and combining it with a supervised learning model to provide ...
0
votes
1answer
91 views

In this paper, if region $R_{2}$ moves in a sliding window manner, won't the saliency map have a smaller size than the original image?

In the paper Salient Region Detection and Segmentation, I have a question pertaining to section 3 on the convolution-like operation being performed. I had already asked a few questions about the paper ...
1
vote
0answers
17 views

What is meant by "spatial encoding" in the context of convolutional neural networks?

Consider the following excerpt from the abstract of the research paper titled Squeeze-and-Excitation networks by Jie Hu et al. Convolutional neural networks are built upon the convolution operation, ...
0
votes
0answers
31 views

Discrepencies between the TimeGan paper and the code?

I recently read the paper Time-Series Generative Neural Networks and found the results that they reported quite promising (https://proceedings.neurips.cc/paper/2019/file/...
1
vote
0answers
12 views

Why actual mapping is called as unreferenced mapping in this context of residual framework?

Consider the following statements from the research paper titled Deep Residual Learning for Image Recognition by Kaiming He et al. #1: We explicitly reformulate the layers as learning residual ...
1
vote
0answers
57 views

What is the derivative of equation 1 in the paper "Conservative Q-Learning for Offline Reinforcement Learning"?

I am looking at the paper Conservative Q-Learning for Offline Reinforcement Learning, but I'm not sure how they proved theorem 3.1. Here is a screenshot of theorem 3.1. In the proof of theorem 3.1 ...
1
vote
2answers
34 views

Why do the authors of the T5 paper say that the "architectural changes are orthogonal to the experimental factors"?

Here's a quote from the T5 paper (T5 stands for "Text-to-Text Transfer Transformer") titled Exploring the Limits of Transfer Learning with a Unified Text-...
1
vote
0answers
44 views

What is the confusion loss for adversarial learning?

What is the confusion loss used in domain adaptation (DA) for adversarial learning/GANs? See this paper. Two domains: $s$: source domain $t$: target domain Generator/Discriminator setting: $M_s:x_s\...
0
votes
0answers
16 views

How did authors ensure that critical points do exist in GAN?

Using an MLP as generator introduces multiple critical points in parameter space. You can read this excerpt from research paper titled Generative Adversarial Nets In practice, adversarial nets ...
0
votes
1answer
39 views

Why disentangling the features of variation in representation?

Consider the following excerpt from abstract of the research paper titled Better Mixing via Deep Representations by Yoshua Bengio et al. It has been hypothesized, ...
1
vote
0answers
19 views

Is the following a typo or am I understanding wrongly regarding discriminator?

Consider the following paragraph from the section 3: Background of the research paper titled Generative Adversarial Text to Image Synthesis by Scott Reed et al. ...
0
votes
1answer
31 views

Where can I access this research paper on Frechet distance score?

Frechet Inception Distance is a metric that calculates the distance between feature vectors calculated for real and generated images. It is used in evaluations how good the generated images are. ...
1
vote
1answer
21 views

Bag of Tricks: n-grams as additional features?

I've been playing with PyTorch's nn.EmbeddingBag for sentence classification for about a month. I've been doing some feature engineering, playing with different ...
0
votes
1answer
86 views

What is the difference between a vision transformer and image based relational learning

I am trying to figure out the difference between the architecture used in this and this paper. It looks like both used multi-headed self-attention and therefore should be the same in principle.
2
votes
1answer
44 views

How is this statement from a TensorFlow implementation of a certain KL-divergence formula related to the corresponding formula?

I am trying to understand a certain KL-divergence formula (which can be found on page 6 of the paper Evidential Deep Learning to Quantify Classification Uncertainty) and found a TensorFlow ...
2
votes
1answer
45 views

What does it mean by strong or sufficient gradient for training in this context?

It has been mentioned in the research paper titled Generative Adversarial Nets that generator need to maximize the function $\log D(G(z))$ instead of minimizing $\log(1 −D(G(z)))$ since the former ...
0
votes
0answers
31 views

Why is the proof of convergence in the GAN paper not applicable practically?

This question is about generative adversarial networks and restricted to the research paper titled Generative Adversarial Nets. If I select a particular architecture of MLP as a generator and trained ...
0
votes
0answers
16 views

Computing the mean attention distance for ViT

Recently I came across the paper that introduces the Vision Transformer (ViT) "AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE". The thing I don't really ...
1
vote
0answers
11 views

What is language-conditioned visual reasoning?

Can anyone explain what language-conditioned visual reasoning is? I saw this term in this paper and I searched on the internet but I couldn't find a proper explanation.
1
vote
0answers
14 views

What does the lambda parameter in the paper "Interpretable Explanations of Black Boxes by Meaningful Perturbation" do?

I do not understand the purpose of the $\lambda$ parameter in equation 3 of the paper Interpretable Explanations of Black Boxes by Meaningful Perturbation. $$m^{*}=\underset{m \in[0,1]^{\Lambda}}{\...
1
vote
0answers
23 views

Is label-embedding similar to one-hot encoding?

In one-hot encoding, a vector is given to each class label. For each class, only one entry of the vector is equal to 1 and the remaining entries are zeros in this encoding. Thus, in one-hot encoding, ...
1
vote
1answer
27 views

Could someone help tell what the labels are pointed out by red rectangles?

The following figure comes from the paper The perceptron: A probabilistic model for information storage and organization in the brain I can tell the labels pointed out by blue rectangles are: "...
0
votes
0answers
11 views

What are some of the ideas to solve Learning-to-choose problem?

Suppose I want to predict cats and dogs, but with a twist: the model can choose the image to predict. For example: Given a list of 10 images (with both dogs and cats), the model need to choose one ...
1
vote
3answers
172 views

Why is AI Super Resolution Reconstruction more than just guessing?

I saw a video on Youtube about AI and Super Resolution Image Reconstruction with TecoGAN. I must say I am impressed. Now, I am wondering how reliable this is. I have learned at university that you ...
0
votes
0answers
17 views

Naming convention for deep learning layer sequences ("FC7", "Conv-1-3")

I was looking at the deep learning paper A Target-agnostic Attack on Deep Models and saw this figure (figure 3 on paper) demonstrating the performance of a transfer-learning-based adversarial attack ...
0
votes
1answer
42 views

How does CURL extract labels from logits?

While going over the pseudocode of the CURL paper, the method to identify labels from the logits wasn't clear to me. I believe this technique might be common in other PyTorch/Deep Learning tasks. I ...
1
vote
0answers
23 views

Why class embedding token is added to the Visual Transformer?

In the famous work on the Visual Transformers, the image is split into patches of a certain size (say 16x16), and these patches are treated as tokens in the NLP tasks. In order to perform ...
1
vote
1answer
20 views

What to do when the ROIs are smaller than $227 \times 227$ in R-CNN?

As English is not my native language, I have some hard time understanding the following sentence: Regardless of the size or aspect ratio of the candidate region, we warp all pixels in a tight ...
1
vote
0answers
21 views

Is there any work that applies the approach in "Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms" to standard Q-learning?

I am trying to mathematically characterize the finite sample convergence rates for Q-learning. To this end, I have read the following papers Learning rates for Q-learning, by Eyal Even-Dar et al.; ...
0
votes
1answer
74 views

What is the difference between the definition of "accuracy" in machine learning and federated learning?

What is the difference between the definition of "accuracy" in machine learning and federated learning? In particular, how is the accuracy calculated in the following paper: Cai, Lingshuang,...
1
vote
0answers
16 views

What's mutual exclusivity in meta-learning?

What do we mean by mutual exclusivity of tasks? This work (E Pan, 21) and this one (M Yin, 20) state that most classification meta-learning algorithms fail for non-mutually exclusive tasks as the ...
0
votes
0answers
30 views

How to choose the reward in reinforcement learning? [duplicate]

I am solving a combinatorial optimization problem, where I do not have a global optimum, so the goal is to improve the objective function as much as possible. So, to do this, I was inspired by this ...
0
votes
0answers
13 views

Why do the authors of this paper down-sample by $ds_1 / 2$ (in the context of coarse-to-fine segmentation)?

This question is a follow-up of this post and based on this paper. In section 2.2, the authors write: In the first level, the 3D FCN is trained on images of the lowest resolution in order to capture ...
2
votes
0answers
24 views

What is meant by Hinton when he refers to "Part-Whole Hierarchies" in his GLOM framework

I was recently reading Hinton's GLOM idea How to represent part-whole hierarchies in a neural network, and I am simply unsure about what exactly he means when he says parsing images into "part-...
0
votes
0answers
12 views

How exactly is masking performed in the training part of the paper "Semi-Supervised Classification with Graph Convolutional Networks"?

I am struggling to understand the training part of the paper Semi-Supervised Classification with Graph Convolutional Networks (2017) by Thomas Kipf and Max Welling. The GitHub repo is here. I do not ...
1
vote
1answer
26 views

Why the non-exploitation of edge labels in current graph convolutions "results in an overly homogeneous view of local graph neighborhoods"?

I am currently reading a paper called Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs (2017, CPPR), and I cannot understand the following sentence: We identify that the ...
1
vote
1answer
38 views

Understanding Generalized Advantage Estimate in reinforcement learning

I was reading the paper on Generalized Advantage Estimate. It first introduces a generalized form of policy gradient equation without involving $\gamma$ and then it says the following: We will ...
3
votes
2answers
68 views

Why some neural network models in the 1980s shown as circuit models

I am familiar with the currently popular neural network models that have weights and are trained with backpropagation and gradient descent. However, I came across a different type of neural network ...
1
vote
1answer
24 views

How is the variational lower bound for hard attention derived in Show, Attend and Tell

How is the jump from line 1 to line 2 done in equation 10 of Show, Attend and Tell? While we're at it, another thing that might be muddying the waters for me is that I'm not clear on what the sum is ...
0
votes
0answers
24 views

Do $V_\theta$ and $V_s$ represent partial or total derivatives in the paper "Learning Continuous Control Policies by Stochastic Value Gradients"?

I was reading up on the Stochastic Value Gradients paper by Heess et al. In the paper, they describe a recursive process to calculate path-wise derivatives via equations (3) and (4), at the bottom of ...
1
vote
0answers
31 views

What is a Hebbian linear classifier?

I was reading Deep Learning of Representations for Unsupervised and Transfer Learning, and they state the following: They have only a small number of unlabeled examples (4096) and very few labeled ...
6
votes
2answers
116 views

What does "semantic gap" mean?

I was reading DT-LET: Deep transfer learning by exploring where to transfer, and it contains the following: It should be noted direct use of labeled source domain data on a new scene of target domain ...
0
votes
0answers
67 views

Comparing heuristics in A* search and rescue operation

I was reading a research paper titled A Comparative Study of A-star Algorithms for Search and rescue in Perfect Maze (2011). I have some doubts regarding it: 1. The Evaluation Function of $\mathrm{A}^...
1
vote
2answers
75 views

In variational autoencoders, what does p(x|z) mean?

If $x \sim \mathcal{N}(\mu,\,\sigma^{2})$, then it is a continuous variable, and therefore $P(x) = 0$ for any x. One can only consider things like $P(x<X)$ to get a probability greater than 0. So ...
1
vote
0answers
18 views

Clonal operator in Immune Clonal Strategy

I was reading about Immune Clonal Strategy, specifically about Monoclonal operator from Immunity clonal strategies, and it goes as follows: Here $a_i $ is a point and $a_i = \{ x_1, x_2, \cdots, x_m \...
1
vote
0answers
25 views

What is the meaning of "Our current objective weights every token equally and lacks a notion of what is most important to predict" in the GPT-3 paper?

On page 34 of OpenAI's GPT-3, there is a sentence demonstrating the limitation of objective function: Our current objective weights every token equally and lacks a notion of what is most important to ...
2
votes
0answers
71 views

How many papers about AI / ML were published in the recent years?

I am trying to formulate an argument at work saying the disruption in AI/ML is very high and that it is hard to stay "state of the art". I would like to support that hypothesis by numbers. ...

1
2 3 4 5