Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
For future learning systems, incremental learning is desirable because it allows for: efficient resource usage by eliminating the need to retrain from scratch at the arrival of new data; reduced memor...
Open Artificial Intelligence (AI) published an AI chatbot tool called ChatGPT at the end of November 2022. • Specific features and capabilities of the ChatGPT support system are elaborated in this pap...
ABSTRACT We develop FinBERT, a state‐of‐the‐art large language model that adapts to the finance domain. Last, we show that other approaches underestimate the textual informativeness of earnings confer...
Deep reinforcement learning (DRL) integrates the feature representation ability of deep learning with the decision-making ability of reinforcement learning so that it can achieve powerful end-to-end l...
This research explores Multimodal sentiment analysis: A systematic review of histor..., contributing new insights to the field of Artificial Intelligence.
This research explores Application of explainable artificial intelligence for healt..., contributing new insights to the field of Artificial Intelligence.
Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Especially, we get 44.98%, 38.42% and...
Inductive/deductive hybrid thematic analysis offers significant opportunities for researchers, but its application within integrative mixed methods research has yet to be fully explored. Here, the cri...
Computational Intelligence and Neuroscience is a forum for the interdisciplinary field of neural computing, neural engineering and artificial intelligence.
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Ro...
This research explores Challenges and opportunities in quantum machine learning, contributing new insights to the field of Artificial Intelligence.
This article surveys and organizes research works in a new paradigm in natural language processing, which we dub “prompt-based learning.” Unlike traditional supervised learning, which trains a model t...
This research explores TransMorph: Transformer for unsupervised medical image regis..., contributing new insights to the field of Artificial Intelligence.
We present ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification. Finally, by adapting our model to machine translation we achieve surprisingly good results.
For years, the YOLO series has been the de facto industry-level standard for efficient object detection. We carefully conducted experiments to validate the effectiveness of each component.
Deep Residual Networks have recently been shown to significantly improve the performance of neural networks trained on ImageNet, with results beating all previous methods on this dataset by large marg...
This research explores Count (and count-like) data in finance, contributing new insights to the field of Artificial Intelligence.
As our dependence on intelligent machines continues to grow, so does the demand for more transparent and interpretable models. Additionally, concrete examples are used to describe these techniques tha...
The increasing availability of biomedical data from large biobanks, electronic health records, medical imaging, wearable and ambient biosensors, and the lower cost of genome and microbiome sequencing...
This paper discusses two important limitations of the common practice of testing for preexisting differences in trends (“ pre-trends”) when using difference-in-differences and related methods. I analy...