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**A**: see [4]).
The topology-free approach takes into account the cardinality of the basic set A𝐴Aitalic_A and the arity of operations**B**: This approach is widely followed in the literature (e.g**C**: Bruno Poizat fully developed the topology-free approach in [19]. In [20, 21] R. Pöschel characterised the Galois cl... | CAB | BAC | CBA | ABC | Selection 2 |
**A**: The proof is split into three parts**B**: In Section 5, we prove that the decision version of Min-k𝑘kitalic_k-DMC is already NP-hard when k=3𝑘3k=3italic_k = 3**C**: First, we show that a variant of the constrained minimum vertex cover problem on bipartite graphs (Min-CVCB) of Chen and Kanj [CK03] is NP-hard. T... | BCA | BAC | BCA | CBA | Selection 2 |
**A**: The advantage to the topological approach used in this paper is that a very general topology can be used**B**: The only assumption needed is that the topology needs to have the T0subscript𝑇0T_{0}italic_T start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT property and a computable countable basis**C**: Typical requirements... | CAB | ACB | ABC | CAB | Selection 3 |
**A**: As deep neural networks require a certain amount of labeled data for effective training, it is well known that the lack of a large enough corpus of accurately labeled high-quality data can produce disappointing results. Data augmentation [23] is one way to overcome this problem**B**: The goal of this approach is... | BCA | CBA | ACB | CBA | Selection 3 |
**A**: To examine the impact of the number of classes, we show the results using C∈{200,300,500,1000}𝐶2003005001000\mathit{C}\in\{200,300,500,1000\}italic_C ∈ { 200 , 300 , 500 , 1000 } randomly selected ID classes from ImageNet-1k (C=1000𝐶1000C=1000italic_C = 1000 is the full ImageNet-1k data).**B**: Another challen... | BAC | CBA | CAB | CBA | Selection 3 |
**A**: We propose using a conditional diffusion model in order to model the distribution between under-exposed and normally-exposed images. Further, we introduce a method of applying the diffusion model as a post-processing technique. Our approach uses the diffusion model to estimate the amount of noise present in an e... | CBA | BAC | BAC | BCA | Selection 4 |
**A**: Our results have far-reaching implications**B**: When it comes to government practices of digital services, the concept of "online only" has already been challenged by scholars relying on the fact that people of certain characteristics, particularly age, are less likely to be able to get online, and therefore th... | BCA | ABC | BAC | CAB | Selection 2 |
**A**: These comparisons validate the superior structural representation capabilities by a large margin (Ours: 16.8%P@1, 31.3%P@2, 40.2%P@3). We employ ESM-2 as a language modality input for comparison to confirm its sequence-only representation capabilities. Although ESM-2 (11.5%P@1, 24.5%P@2, 36.5%P@3) slightly outpe... | BAC | BCA | BCA | CBA | Selection 4 |
**A**: The experiment is conducted on the largest FB15K237 dataset, with accuracy measured by MRR. Specifically, we include LiftNet variants of 2 to 4 FC layers, and the results are shown in Table IX**B**:
In LiftNet, we adopt TC layers to progressively lift the dimensions. To demonstrate the effectiveness of such a d... | BAC | ACB | BCA | ABC | Selection 1 |
**A**: This represents the biggest drawback of using linear programming for entanglement routing: the amount of detail one can add becomes restricted by the need to formulate the problem as a linear optimization**B**: Unfortunately, to the best of our knowledge, our problem cannot be formulated as a linear programming ... | BCA | BAC | ABC | BCA | Selection 2 |
**A**: We first prove that the ML performance can approach the MWUB as the SNR goes to infinity**B**: Then, we design the ordered and nested MWD sequence to apply fast construction without channel information and we prove that the MWD sequence is the optimum sequence evaluated by MWUB for polar codes obeying PO. Finall... | ABC | BCA | ABC | CAB | Selection 2 |
**A**:
where the inequality follows from our assumption 1/2<p<112𝑝11/2<p<11 / 2 < italic_p < 1**B**: So for this tree we have that the mean depth is given by**C**: Thus we see that when there are signals the weights on leaf nodes are no longer proportional, but skewed further towards the longer branches | ABC | CBA | ACB | BAC | Selection 3 |
**A**: Several other works studied text-to-image latent diffusion models for medical imaging Chambon et al**B**: (2023).
Closest to our work is Chambon et al. (2022b), where the authors explore various methods to adapt a pre-trained Stable Diffusion model to chest X-ray generation.**C**: (2022a); Akrout et al | BCA | ABC | ACB | CBA | Selection 3 |
**A**: During optimization, the camera field of view is randomly sampled between 40 and 70 degrees. At test time, the field of view is fixed at 60 degrees.**B**: The camera distance can also be scaled in the way discussed in the main paper**C**: Plus,
cameras are oriented to look toward the objects | BAC | CAB | CBA | BAC | Selection 2 |
**A**: Additionally, both figures show how our cluster overlap relates to the silhouette score, a popular metric for quantifying clustering difficulty (Rousseeuw, (1987), Shand et al., (2019)). At a fixed value of max_overlap, the silhouette score decreases markedly with a rise in dimensionality**B**: This is not an ar... | CBA | CAB | BCA | CBA | Selection 3 |
**A**: Our COFFEE introduces a contrastive selector to improve trigger extraction performance by re-ranking and automatically determining the number of triggers to be selected in a given context. Additionally, we investigate the dependence of current generation-based models on extra knowledge, such as designed event-sp... | BCA | BAC | BAC | CBA | Selection 1 |
**A**: For details of interpolation of Banach spaces through the real method, we refer to Sawano (2018, Chapter 4.2.2)**B**:
It is worth pointing out the relation between the definition (5) and the interpolation space defined through the real method (real interpolation)**C**: Specifically, Steinwart and Scovel (2012, ... | ACB | BAC | ABC | ACB | Selection 2 |
**A**: This would allow occluded as well as outlier-ridden extremely noisy point clouds, where the original observations do not necessarily lie on the true surface of the manifold, to be denoised and/or simplified.
**B**: However, this assumption could be relaxed and sparse GPs can be used to perform continuous optimiz... | BAC | CBA | ACB | CAB | Selection 2 |
**A**: In Fig. 2, we observe that employing adaptive learning rates on the first-order optimization algorithms is instrumental in enhancing the efficiency of FL models, especially for the large-scale FL optimization tasks, as highlighted in [14]. Fig. 2 shows a quantitative analysis of model accuracy and training loss ... | CBA | CBA | BAC | CAB | Selection 4 |
**A**:
ScienceQA (Lu et al., 2022) Evaluation**B**: ScienceQA includes a large-scale science question answering data collected from a wide range of knowledge domains**C**: Each sample contains a visual context, a textual context, a question with multiple options, and an answer. We directly utilize ScienceQA’s multi-mo... | BAC | BAC | ABC | CBA | Selection 3 |
**A**: It takes about one day for the whole pre-training stage.**B**: We implement S-ViLM in JAX and train all models on TPU accelerators**C**: During pre-training, SGD with momentum 0.9 and initial learning rate 0.1 is used for optimization.
We train S-ViLM for 10 epochs with a batch size 1024 and adopt a cosine learn... | CAB | CBA | BAC | BAC | Selection 1 |
**A**: (2019) showed that adding too many layers to a convolutional neural network, trained for image classification, hurts its performance**B**: Many studies have used similarity measures for the interpretability of NNs.
For instance, Kornblith et al**C**: Using CKA, they found that more than half of the network’s lay... | ABC | BAC | ACB | BCA | Selection 2 |
**A**: (a) Results of conventional methods**B**: From left to right: input images, GT images, and results of López-Antequera et al. [36], Wakai and Yamashita [58], Wakai et al. [59], Pritts et al. [44], and Lochman et al. [35]. (b) Results of our method. From left to right: input images, GT images, and the results of o... | CAB | CAB | BAC | BCA | Selection 4 |
**A**: We first prove the equivalence among statements (i), (ii) and (iii)**B**: To show the equivalence of the six statements in Theorem 1, the proof is structured as follows**C**: Then, we prove the following chain of implications:
(iii) ⟹⟹\Longrightarrow⟹ (iv), followed by (iv) ⟹\implies⟹ (v), (v) ⟹\implies⟹ (vi), a... | CBA | ACB | ABC | BAC | Selection 4 |
**A**: Quantitatively (Spearman), results are similar.
The test yields a weak positive correlation (ρ=0.34𝜌0.34\rho=0.34italic_ρ = 0.34)**B**: Qualitatively, in Figure 6 we see no discernible increase in the number of failures following larger ONNX updates**C**: Similarly, Incompatibility and Type Problems | CBA | CBA | BAC | ACB | Selection 3 |
**A**: The Alphanumeric Viewer is a component that monitors the state of specific variables of the system, e.g**B**: The information is distributed in different panes to facilitate the search for a specific variable of the system.
On the other hand, tools like the Keyboard teleoperation are useful to manipulate the dro... | ABC | BAC | CAB | ACB | Selection 4 |
**A**: Notwithstanding, it is not obvious whether these “machines” are truly creative, at least in the sense originally discussed by Ada Lovelace (Menabrea and Lovelace, 1843)**B**: LLMs have already been analyzed (and sometimes criticized) from different perspectives, e.g., fairness (Bender et al., 2021), concept unde... | ACB | ACB | ACB | BCA | Selection 4 |
**A**: These approaches mainly focus on exploiting the source model**B**: (b) Our proposed SUP-ICI utilizes instance-level contrastive learning (CL) to make use of the foreground-background semantic information of the unlabeled target images. Our weighted entropy (WE) loss is also incorporated for label denoising.
**C*... | CBA | CBA | BCA | ABC | Selection 3 |
**A**: The two-stage DCOPF problem is also becoming increasingly popular as a canonical problem that incorporates the impact of uncertainties arising from renewable resources [9, 10]. In more general terms, the two-stage DCOPF problem falls under the category of two-stage stochastic linear programs with (fixed) recours... | BCA | BAC | CAB | ABC | Selection 3 |
**A**: We use predictive entropy for SimCLR, which does not provide epistemic uncertainty estimates.
Mean and std. shown (3 seeds)**B**: For the self-supervised BNN and the ensemble, we acquire points with BALD**C**: The methods that incorporate unlabelled data perform best by far, with our method slightly outperformin... | BAC | ABC | CBA | ACB | Selection 1 |
**A**: This result is particularly useful because even though the underlying metric measure dynamical system need not satisfy the necessary assumptions, (e.g., is not finite-dimensional or approximable by finite-dimensional spaces)
the target spaces for most stable shape descriptors used in practice do.**B**: Indeed, u... | CBA | ACB | ABC | BAC | Selection 1 |
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