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Found 9 papers, 1 papers with code
Adversarial Data Augmentation for Robust Speaker Verification
This adversarial learning empowers the network to generate speaker embeddings that can deceive the augmentation classifier, making the learned speaker embeddings more robust in the face of augmentation variations.
Fast ODE-based Sampling for Diffusion Models in Around 5 Steps
Sampling from diffusion models can be treated as solving the corresponding ordinary differential equations (ODEs), with the aim of obtaining an accurate solution with as few number of function evaluations (NFE) as possible.
A Geometric Perspective on Diffusion Models
Recent years have witnessed significant progress in developing effective training and fast sampling techniques for diffusion models.
HDR Video Reconstruction with a Large Dynamic Dataset in Raw and sRGB Domains
Based on this dataset, we further propose a Raw-HDRNet, which utilizes the raw LDR frames as inputs.
BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation
Integrating LiDAR and Camera information into Bird's-Eye-View (BEV) has become an essential topic for 3D object detection in autonomous driving.
Two-timescale Resource Allocation for Automated Networks in IIoT
The rapid technological advances of cellular technologies will revolutionize network automation in industrial internet of things (IIoT).
Molecular modeling with machine-learned universal potential functions
Molecular modeling is an important topic in drug discovery.
Boosting Gradient for White-Box Adversarial Attacks
Existing white-box attack algorithms can generate powerful adversarial examples.
Prediction of amino acid side chain conformation using a deep neural network
A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy.
