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Found 6 papers, 3 papers with code
A survey on text generation using generative adversarial networks
This work presents a thorough review concerning recent studies and text generation advancements using Generative Adversarial Networks.
Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints
In this work, we study the more challenging open-domain setting consisting of low frequency user prompt patterns (or broad prompts, e. g., prompt about 93rd academy awards) and demonstrate the effectiveness of character-based language models.
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification
Machine Learning has attracted considerable attention throughout the past decade due to its potential to solve far-reaching tasks, such as image classification, object recognition, anomaly detection, and data forecasting.
Learnergy: Energy-based Machine Learners
Throughout the last years, machine learning techniques have been broadly encouraged in the context of deep learning architectures.
OPFython: A Python-Inspired Optimum-Path Forest Classifier
Machine learning techniques have been paramount throughout the last years, being applied in a wide range of tasks, such as classification, object recognition, person identification, and image segmentation.
Stroke lesion detection using convolutional neural networks
Stroke is an injury that affects the brain tissue, mainly caused by changes in the blood supply to a particular region of the brain.
Ranked #1 on
Stroke Classification
on CT Lesion Stroke Dataset
