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Found 9 papers, 4 papers with code
Histo-Genomic Knowledge Distillation For Cancer Prognosis From Histopathology Whole Slide Images
G-HANet is expected to be explored as a useful tool by the research community to address the current bottleneck of insufficient histo-genomic data pairing in the context of cancer prognosis and precision oncology.
Control of Continuous Quantum Systems with Many Degrees of Freedom based on Convergent Reinforcement Learning
Although there have been a few successful applications of deep RL to quantum control problems, most of the existing RL algorithms suffer from instabilities and unsatisfactory reproducibility, and require a large amount of fine-tuning and a large computational budget, both of which limit their applicability.
Quantum Control based on Deep Reinforcement Learning
To our knowledge, this is the first time deep reinforcement learning is applied to quantum control problems in continuous real space.
Multiplex-detection Based Multiple Instance Learning Network for Whole Slide Image Classification
Multiple instance learning (MIL) is a powerful approach to classify whole slide images (WSIs) for diagnostic pathology.
Feature Erasing and Diffusion Network for Occluded Person Re-Identification
With the guidance of the occlusion scores from OEM, the feature diffusion process is mainly conducted on visible body parts, which guarantees the quality of the synthesized NTP characteristics.
Ranked #1 on
Person Re-Identification
on Occluded REID
(Rank-1 metric)
Image-to-Video Generation via 3D Facial Dynamics
Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.
Robust Person Re-Identification through Contextual Mutual Boosting
The mask recalibrates the features to amplify the valuable characteristics and diminish the noise.
Deep Gamblers: Learning to Abstain with Portfolio Theory
We deal with the \textit{selective classification} problem (supervised-learning problem with a rejection option), where we want to achieve the best performance at a certain level of coverage of the data.
Statistical Robust Chinese Remainder Theorem for Multiple Numbers: Wrapped Gaussian Mixture Model
Generalized Chinese Remainder Theorem (CRT) has been shown to be a powerful approach to solve the ambiguity resolution problem.
