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2021-07
Aggregating From Multiple Target-Shifted Sources
2021-05
On the benefits of representation regularization in invariance based domain generalization.
Unified Principles For Multi-Source Transfer Learning Under Label Shifts
2021-04
Recurrent neural networks achieving MLSE performance for optical channel equalization.
2021-03
Meta Learning Black-Box Population-Based Optimizers.
2021-02
A Generative Model for Hallucinating Diverse Versions of Super Resolution Images.
Task Similarity Estimation Through Adversarial Multitask Neural Network
2020-11
Persistent Mixture Model Networks for Few-Shot Image Classification.
2020-07
Beyond H-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence.
Neuronal activity remodels the F-actin based submembrane lattice in dendrites but not axons of hippocampal neurons
2020-06
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities
Deep Active Learning: Unified and Principled Method for Query and Training
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1911.09162 (2019-11-20)]2020-05
Self-supervised Robust Object Detectors from Partially Labelled datasets.
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks
TRACKING AND PREDICTING COVID-19 RADIOLOGICAL TRAJECTORY USING DEEP LEARNING ON CHEST X-RAYS: INITIAL ACCURACY TESTING
2020-02
Improving Policy-Capturing with Active Learning for Real-Time Decision Support
Input Dropout for Spatially Aligned Modalities
2019-12
Associative Alignment for Few-shot Image Classification
2019-11
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift.
2019-10
Toward Metrics for Differentiating Out-of-Distribution Sets
Deep Parametric Indoor Lighting Estimation
ICCV 2019
(2019-10-01)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1910.08812 (2019-10-19)]2019-09
Unsupervised Temperature Scaling: Robust Post-processing Calibration for Domain Shift
Learning of Image Dehazing Models for Segmentation Tasks
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