Due to the importance of zero-shot learning, the number of proposed approaches has increased steadily recently. We argue that it is time to take a step back and to analyze the status quo of the area. The purpose of this paper is three-fold. First, given the fact that there is no agre...
Computational super-resolution methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding performance, however,
In this paper we introduce an online algorithm that uses integral reinforcement knowledge for learning the continuous-time zero sum game solution for nonlinear systems with infinite horizon costs and partial knowledge of the system dynamics. This algorithm is a data based approach to the solution of...
simultaneously in the joint embedding space. The synthesized unseen image data are utilized to construct the classifier for unseen classes. Experimental results show that our method outperforms the state-of-the-art on three popular datasets. The ablation experiment and visualization of the learning ...
This repository contains the testing code for the paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning" accepted to AAAI 2022.We will release all codes of this work later. Preparing Dataset and Model We provide trained models (Google Drive) on three different datasets:CUB,SUN,AW...
In this paper, we propose a zero-shot learning strategy for three-dimensional autonomous endovascular navigation. Using a very small training set of branching patterns, our reinforcement learning algorithm is able to learn a control that can then be applied to unseen vascular anatomies without retrai...
Among panels and conferences featuring Clara Camarasa, Nicola Borregaard, Laura Chapa, Paola Valencia, Iván Osuna, Juan Carlos Vega, Angélica Ospina, and Diego Velandia, five main learnings emerged as lessons: from creating more relevance and energy calculations to the development of the timber in...
This paper investigates the learning behavior of variable-structure stochastic automata in a three person zero-sum game. The game has three variable-structure stochastic automata and a random environment. In the game the players do not possess prior information concerning the payoff matrix and at the...
In short, the plan outlines the measures that will allow us to deliver on the net-zero ambition. The path that leads us there runs through three strategically important areas for Equinor: oil and gas, renewables and low-carbon solutions. These areas are interconnected and must work together fo...
The embedding space can be created by either mapping into a Wikipedia-based semantic representation or learning cross-lingual embeddings. But if the Wikipedia in the target language is small or there is not enough training corpus to train a good embedding space for low-resource languages, then ...