Deep generative models have been an upsurge in the deep learning community since they
were proposed. These models are designed for generating new synthetic data including …

The rise of machine learning has fueled the discovery of new materials and, especially,
metamaterials—truss lattices being their most prominent class. While their tailorable …

Deep learning has revolutionized pattern recognition, introducing tools that power a wide
range of technologies in such diverse fields as computer vision, natural language …

Generative data augmentation (GDA) has emerged as a promising technique to alleviate
data scarcity in machine learning applications. This thesis presents a comprehensive survey …

The process of recognizing and distinguishing between real content and content generated
by deep learning algorithms, often referred to as deepfakes, is known as deepfake detection …

Recent advances in learning reusable motion priors have demonstrated their effectiveness
in generating naturalistic behaviors. In this paper, we propose a new learning framework in …

Two-stage object detectors generate object proposals and classify them to detect objects in
images. These proposals often do not perfectly contain the objects but overlap with them in …

Cognitive diagnosis is an important task in intelligence education, which aims at measuring
students' proficiency in specific knowledge concepts. Given a fully labeled exercise-concept …

Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic
images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lacks …

The style transfer task in Text-to-Speech (TTS) refers to the process of transferring style
information into text content to generate corresponding speech with a specific style …