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09/20/2023
Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation
Few-shot Medical Image Segmentation (FSMIS) is a more promising solution...
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09/09/2023
Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer
Automated segmentation of large volumes of medical images is often plagu...
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06/09/2023
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
Uncertainty quantification (UQ) is important for reliability assessment ...
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04/13/2023
Estimate-Then-Optimize Versus Integrated-Estimation-Optimization: A Stochastic Dominance Perspective
In data-driven stochastic optimization, model parameters of the underlyi...
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11/23/2022
Evolutionary Generalized Zero-Shot Learning
An open problem on the path to artificial intelligence is generalization...
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11/19/2022
Mutual Balancing in State-Object Components for Compositional Zero-Shot Learning
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen composi...
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09/28/2022
Weighted Contrastive Hashing
The development of unsupervised hashing is advanced by the recent popula...
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06/09/2022
Evaluating Aleatoric Uncertainty via Conditional Generative Models
Aleatoric uncertainty quantification seeks for distributional knowledge ...
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06/09/2022
Cardiac Adipose Tissue Segmentation via Image-Level Annotations
Automatically identifying the structural substrates underlying cardiac a...
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04/25/2022
Zero-Shot Logit Adjustment
Semantic-descriptor-based Generalized Zero-Shot Learning (GZSL) poses ch...
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04/24/2022
Towards the Semantic Weak Generalization Problem in Generative Zero-Shot Learning: Ante-hoc and Post-hoc
In this paper, we present a simple and effective strategy lowering the p...
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04/05/2022
Prediction Intervals for Simulation Metamodeling
Simulation metamodeling refers to the construction of lower-fidelity mod...
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01/31/2022
Learning to Hash Naturally Sorts
Locality sensitive hashing pictures a list-wise sorting problem. Its tes...
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01/31/2022
Generalized Bayesian Upper Confidence Bound with Approximate Inference for Bandit Problems
Bayesian bandit algorithms with approximate inference have been widely u...
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12/23/2021
Boosting Generative Zero-Shot Learning by Synthesizing Diverse Features with Attribute Augmentation
The recent advance in deep generative models outlines a promising perspe...
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10/23/2021
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence
Standard Monte Carlo computation is widely known to exhibit a canonical ...
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10/23/2021
Quantifying Epistemic Uncertainty in Deep Learning
Uncertainty quantification is at the core of the reliability and robustn...
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02/26/2021
Learning Prediction Intervals for Regression: Generalization and Calibration
We study the generation of prediction intervals in regression for uncert...
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01/31/2021