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20182023
most citedDeep Learning for Functional Data Analysis with Adaptive Basis Layers

12 citations · 21 across the 5 of their papers we have counts for

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9 papers · 1 filter

cs.LG2023

Estimating label quality and errors in semantic segmentation data via any model

Vedang Lad, Jonas Mueller

The labor-intensive annotation process of semantic segmentation datasets is often prone to errors, since humans struggle to label every pixel correctly. We study algorithms to auto…

cs.LG2023

Detecting Dataset Drift and Non-IID Sampling via k-Nearest Neighbors

Jesse Cummings, Elías Snorrason, Jonas Mueller

We present a straightforward statistical test to detect certain violations of the assumption that the data are Independent and Identically Distributed (IID). The specific form of v…

cs.LG20222 cited

Identifying Incorrect Annotations in Multi-Label Classification Data

Aditya Thyagarajan, Elías Snorrason, Curtis Northcutt +1

In multi-label classification, each example in a dataset may be annotated as belonging to one or more classes (or none of the classes). Example applications include image (or docum…

cs.LG20213 cited

Benchmarking Multimodal AutoML for Tabular Data with Text Fields

Xingjian Shi, Jonas Mueller, Nick Erickson +2

We consider the use of automated supervised learning systems for data tables that not only contain numeric/categorical columns, but one or more text fields as well. Here we assembl…

cs.LG2020

TraDE: Transformers for Density Estimation

Rasool Fakoor, Pratik Chaudhari, Jonas Mueller +1

We present TraDE, a self-attention-based architecture for auto-regressive density estimation with continuous and discrete valued data. Our model is trained using a penalized maximu…

cs.LG2019

Recognizing Variables from their Data via Deep Embeddings of Distributions

Jonas Mueller, Alex Smola

A key obstacle in automated analytics and meta-learning is the inability to recognize when different datasets contain measurements of the same variable. Because provided attribute…