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06/21/2023
Semi-Implicit Denoising Diffusion Models (SIDDMs)
Despite the proliferation of generative models, achieving fast sampling ...
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05/23/2023
From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding
Current state-of-the-art models for natural language understanding requi...
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10/21/2022
Augmentation by Counterfactual Explanation – Fixing an Overconfident Classifier
A highly accurate but overconfident model is ill-suited for deployment i...
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06/28/2022
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation
An organ segmentation method that can generalize to unseen contrasts and...
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01/08/2022
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation
Domain Adaptation (DA) has recently raised strong interests in the medic...
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08/19/2021
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision
Deep learning has achieved remarkable success in medicalimage segmentati...
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07/10/2021
Using Causal Analysis for Conceptual Deep Learning Explanation
Model explainability is essential for the creation of trustworthy Machin...
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01/13/2021
Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
Vessel segmenting is an essential task in many clinical applications. Al...
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01/11/2021
Explaining the Black-box Smoothly- A Counterfactual Approach
We propose a BlackBox Counterfactual Explainer that is explicitly develo...
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06/01/2020
Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space
Learning accurate drug representation is essential for tasks such as com...
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11/01/2019
Explanation by Progressive Exaggeration
As machine learning methods see greater adoption and implementation in h...
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10/14/2019
Robust Ordinal VAE: Employing Noisy Pairwise Comparisons for Disentanglement
Recent work by Locatello et al. (2018) has shown that an inductive bias ...
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07/16/2019
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach
Majority of state-of-the-art monocular depth estimation methods are supe...
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07/05/2019
Twin Auxiliary Classifiers GAN
Conditional generative models enjoy remarkable progress over the past fe...
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06/03/2019
Weakly Supervised Disentanglement by Pairwise Similarities
Recently, researches related to unsupervised disentanglement learning wi...
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04/02/2019
Generative-Discriminative Complementary Learning
Majority of state-of-the-art deep learning methods for vision applicatio...
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01/21/2019
Robust Angular Local Descriptor Learning
In recent years, the learned local descriptors have outperformed handcra...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/08/2018
Deep Diffeomorphic Normalizing Flows
The Normalizing Flow (NF) models a general probability density by estima...
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09/16/2018
Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping
Unsupervised domain mapping aims at learning a function to translate dom...
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06/06/2018
Deep Ordinal Regression Network for Monocular Depth Estimation
Monocular depth estimation, which plays a crucial role in understanding ...
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04/12/2018
Causal Generative Domain Adaptation Networks
We propose a new generative model for domain adaptation, in which traini...
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06/10/2017
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions
Measurement error in the observed values of the variables can greatly ch...
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04/01/2016
