Machine learning-based unfolding has enabled unbinned and high-dimension...
We propose an efficient approach to train large diffusion models with ma...
Deep learning models have been widely used in commercial acoustic system...
We propose Image-to-Image Schrödinger Bridge (I^2SB), a new class of
con...
Augmenting pretrained language models (LMs) with a vision encoder (e.g.,...
Diffusion models have found widespread adoption in various areas. Howeve...
Diffusion models have been recently employed to improve certified robust...
Molecular complexes formed by proteins and small-molecule ligands are
ub...
Pre-trained vision-language models (e.g., CLIP) have shown promising
zer...
Generating new molecules with specified chemical and biological properti...
3D Point cloud is becoming a critical data representation in many real-w...
A significant gap remains between today's visual pattern recognition mod...
Adversarial purification refers to a class of defense methods that remov...
Reasoning about visual relationships is central to how humans interpret ...
Controllable generation is one of the key requirements for successful
ad...
Humans have an inherent ability to learn novel concepts from only a few
...
Learning interpretable and disentangled representations is a crucial yet...
Disentanglement learning is crucial for obtaining disentangled
represent...
Generative adversarial networks (GANs) are notoriously difficult to trai...
Backpropagation-based visualizations have been proposed to interpret
con...