Max Horn | DeepAI

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∙ 04/20/2023

A data augmentation perspective on diffusion models and retrieval

Diffusion models excel at generating photorealistic images from text-que...

0 Max F. Burg, et al. ∙

∙ 01/12/2023

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning

Recent years have seen a surge of interest in learning high-level causal...

7 Yuejiang Liu, et al. ∙

∙ 09/29/2022

Bridging the Gap to Real-World Object-Centric Learning

Humans naturally decompose their environment into entities at the approp...

38 Maximilian Seitzer, et al. ∙

∙ 07/19/2022

Assaying Out-Of-Distribution Generalization in Transfer Learning

Since out-of-distribution generalization is a generally ill-posed proble...

6 Florian Wenzel, et al. ∙

∙ 10/08/2021

Pathologies in priors and inference for Bayesian transformers

In recent years, the transformer has established itself as a workhorse i...

0 Tristan Cinquin, et al. ∙

∙ 07/12/2021

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning

Despite decades of clinical research, sepsis remains a global public hea...

2 Michael Moor, et al. ∙

∙ 06/02/2021

Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions

Graph generative models are a highly active branch of machine learning. ...

51 Leslie O'Bray, et al. ∙

∙ 02/15/2021

Topological Graph Neural Networks

Graph neural networks (GNNs) are a powerful architecture for tackling gr...

68 Max Horn, et al. ∙

∙ 02/15/2021

Translational Equivariance in Kernelizable Attention

While Transformer architectures have show remarkable success, they are b...

0 Max Horn, et al. ∙

∙ 05/25/2020

Path Imputation Strategies for Signature Models

The signature transform is a 'universal nonlinearity' on the space of co...

10 Michael Moor, et al. ∙

∙ 09/26/2019

Set Functions for Time Series

Despite the eminent successes of deep neural networks, many architecture...

0 Max Horn, et al. ∙

∙ 06/03/2019

Topological Autoencoders

We propose a novel approach for preserving topological structures of the...

1 Michael Moor, et al. ∙

∙ 04/16/2019

Machine learning for early prediction of circulatory failure in the intensive care unit

Intensive care clinicians are presented with large quantities of patient...

0 Stephanie L. Hyland, et al. ∙

∙ 02/05/2019

Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis

Motivation: Sepsis is a life-threatening host response to infection asso...

0 Michael Moor, et al. ∙

∙ 12/23/2018

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

While many approaches to make neural networks more fathomable have been ...

16 Bastian Rieck, et al. ∙