Picture for Kalliopi Basioti

Kalliopi Basioti

Visual Semantic Parsing: From Images to Abstract Meaning Representation

Oct 27, 2022
Mohamed Ashraf Abdelsalam, Zhan Shi, Federico Fancellu, Kalliopi Basioti, Dhaivat J. Bhatt, Vladimir Pavlovic, Afsaneh Fazly

Figure 1 for Visual Semantic Parsing: From Images to Abstract Meaning Representation

Figure 2 for Visual Semantic Parsing: From Images to Abstract Meaning Representation

Figure 3 for Visual Semantic Parsing: From Images to Abstract Meaning Representation

Figure 4 for Visual Semantic Parsing: From Images to Abstract Meaning Representation

* published in CoNLL 2022

Access Paper or Ask Questions

Image De-Quantization Using Generative Models as Priors

Jul 17, 2020
Kalliopi Basioti, George V. Moustakides

Figure 1 for Image De-Quantization Using Generative Models as Priors

Figure 2 for Image De-Quantization Using Generative Models as Priors

Figure 3 for Image De-Quantization Using Generative Models as Priors

Figure 4 for Image De-Quantization Using Generative Models as Priors

Access Paper or Ask Questions

Image Restoration from Parametric Transformations using Generative Models

Jun 16, 2020
Kalliopi Basioti, George V. Moustakides

Figure 1 for Image Restoration from Parametric Transformations using Generative Models

Figure 2 for Image Restoration from Parametric Transformations using Generative Models

Figure 3 for Image Restoration from Parametric Transformations using Generative Models

Access Paper or Ask Questions

Designing GANs: A Likelihood Ratio Approach

Feb 06, 2020
Kalliopi Basioti, George V. Moustakides

Figure 1 for Designing GANs: A Likelihood Ratio Approach

Figure 2 for Designing GANs: A Likelihood Ratio Approach

Figure 3 for Designing GANs: A Likelihood Ratio Approach

Figure 4 for Designing GANs: A Likelihood Ratio Approach

Access Paper or Ask Questions

Training Neural Networks for Likelihood/Density Ratio Estimation

Nov 05, 2019
George V. Moustakides, Kalliopi Basioti

Figure 1 for Training Neural Networks for Likelihood/Density Ratio Estimation

Figure 2 for Training Neural Networks for Likelihood/Density Ratio Estimation

Figure 3 for Training Neural Networks for Likelihood/Density Ratio Estimation

Figure 4 for Training Neural Networks for Likelihood/Density Ratio Estimation

Access Paper or Ask Questions

Optimizing Shallow Networks for Binary Classification

May 24, 2019
Kalliopi Basioti, George V. Moustakides

Figure 1 for Optimizing Shallow Networks for Binary Classification

Figure 2 for Optimizing Shallow Networks for Binary Classification

Figure 3 for Optimizing Shallow Networks for Binary Classification

Figure 4 for Optimizing Shallow Networks for Binary Classification

Access Paper or Ask Questions