Abstract Several researchers have investigated the consequences of using ChatGPT in the education industry. Their findings raised doubts regarding the probable effects that ChatGPT may have on the academia. As such, the present study aimed to assess the ability of three methods, namely: (1) academ...
Using the Weyl-type character formula developed in [15], together with the explicit presentation of the weight spaces of the fundamental representations of\mathfrak {g}, as well as some technical calculations involving the central characters of the folded quantum torus algebra, we compute explicitly...
In the aftermath of the groundbreaking research of [21], several studies explored the environment-growth linkage under the auspices of the Environmental Kuznets Curve (EKC). The conclusions of these studies have been mixed as some argue its invalidity [22], and others support its existence with ...
. Therefore, theunder the optimal policyis greater than or equal to theunder any other policyfor all states and actions. In other words, for every state, the optimal policyshould specify the action that leads to the highest expected cumulative reward. In practical circumstances where traversing a...
minimizes the mean squared error (MSE). We repeat this experiment with two different pre-trained and freely available word embeddings: FastText crawl-300d-2M-subword (https://fasttext.cc/docs/en/english-vectors.html last accessed on 15 September 2022), which contains two million words with the...
The size of a matrix is defined by the number of rows and columns. A matrix with m rows and n columns is called an m×n matrix. A raw vector in Rm is a 1×m matrix [a1a2a3…an].A matrix with equal number of rows and columns is commonly known as a squared matrix. Several ...
CLIP的image transformation只用了resize和squared crop; CLIP loss中的temperature参数τ是可学的。 于是CLIP的预训练模型就有了: 一个batch里有N对(image,text),然后和ConVIRT一样做对称的contrastive learning,伪代码如下: 3.2 Inference / Zero-shot prediction 一旦CLIP训练好了,我们就可以做zero-shot prediction了...
CLIP的image transformation只用了resize和squared crop；CLIP loss中的temperature参数τ是可学的。于是CLIP...
The DQN algorithm alternates between gradient descent and data collection to minimize the mean-squared temporal difference (TD) error objective: $$\begin{aligned} L(\theta _i)={\mathbb {E}}_{s_t,a_t\sim D}[(y-Q(s_t,a_t;\theta _i))^2], \end{aligned}$$ (4) which is a ...
as well as test loss and root mean squared error (RMSE) for regression tasks. The pretrained models were evaluated on several tasks using fine-tuning datasets from MoleculeNet [7]. However, most existing datasets struggle with complex tasks owing to data scarcity issues and highly imbalanced class...