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Found 6 papers, 2 papers with code
TKwinFormer: Top k Window Attention in Vision Transformers for Feature Matching
Local feature matching remains a challenging task, primarily due to difficulties in matching sparse keypoints and low-texture regions.
Learning to Maximize Mutual Information for Dynamic Feature Selection
Feature selection helps reduce data acquisition costs in ML, but the standard approach is to train models with static feature subsets.
A Deep Bayesian Bandits Approach for Anticancer Therapy: Exploration via Functional Prior
Learning personalized cancer treatment with machine learning holds great promise to improve cancer patients' chance of survival.
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients
The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari.
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes
Counterfactual prediction is a fundamental task in decision-making.
A Biologically Plausible Benchmark for Contextual Bandit Algorithms in Precision Oncology Using in vitro Data
Here, we propose a benchmark dataset to evaluate contextual bandit algorithms based on real in vitro drug response of approximately 900 cancer cell lines.
