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Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive Loss
DongseokShim, H.JinKim....
Published date-11/06/2020
DepthEstimation, MonocularDepthEstimation, ObjectDetection, Self-SupervisedLearning
Estimating a depth map from a single RGB image has been investigated widely for localization, mapping, and 3-dimensional object detection. Recent studies on a single-view depth estimation are mostly based …
Feature Removal Is a Unifying Principle for Model Explanation Methods
IanCovert, ScottLundberg, Su-InLee....
Published date-11/06/2020
Researchers have proposed a wide variety of model explanation approaches, but it remains unclear how most methods are related or when one method is preferable to another. We examine the …
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data
DennisUlmer, LottaMeijerink, GiovanniCinà....
Published date-11/06/2020
When deploying machine learning models in high-stakes real-world environments such as health care, it is crucial to accurately assess the uncertainty concerning a model's prediction on abnormal inputs. However, there …
Deep Transfer Learning for Automated Diagnosis of Skin Lesions from Photographs
EmmaRocheteau, DoyoonKim....
Published date-11/06/2020
TransferLearning
Melanoma is not the most common form of skin cancer, but it is the most deadly. Currently, the disease is diagnosed by expert dermatologists, which is costly and requires timely …
From Dataset Recycling to Multi-Property Extraction and Beyond
TomaszDwojak, MichałPietruszka, ŁukaszBorchmann....
Published date-11/06/2020
MachineReadingComprehension, ReadingComprehension
This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outperforms the current state-of-the-art by a large margin. Next, we …
User-Dependent Neural Sequence Models for Continuous-Time Event Data
AlexBoyd, RobertBamler, StephanMandt....
Published date-11/06/2020
VariationalInference
Continuous-time event data are common in applications such as individual behavior data, financial transactions, and medical health records. Modeling such data can be very challenging, in particular for applications with …