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Found 5 papers, 2 papers with code
Fishr: Invariant Gradient Variances for Out-of-distribution Generalization
In this paper, we introduce a new regularization -- named Fishr -- that enforces domain invariance in the space of the gradients of the loss: specifically, the domain-level variances of gradients are matched across training domains.
Ranked #10 on
Domain Generalization
on Office-Home
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks
Recent strategies achieved ensembling "for free" by fitting concurrently diverse subnetworks inside a single base network.
Ranked #6 on
Image Classification
on Tiny ImageNet Classification
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Deep ensembles perform better than a single network thanks to the diversity among their members.
CORE: Color Regression for Multiple Colors Fashion Garments
The second stage combines a colorname-attention (dependent of the detected color) with an object-attention (dependent of the clothing category) and finally weights a spatial pooling over the image pixels' RGB values.
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation
Similarly to self-training methods, the predictions of these initial detectors mitigate the missing annotations on the complementary datasets.
