Search Results for author: Prateek Katiyar

Found 4 papers, 2 papers with code

ResNet After All: Neural ODEs and Their Numerical Solution

no code implementations ICLR 2021 Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann

If the trained model is supposed to be a flow generated from an ODE, it should be possible to choose another numerical solver with equal or smaller numerical error without loss of performance.

valid

Improving Augmentation and Evaluation Schemes for Semantic Image Synthesis

no code implementations25 Nov 2020 Prateek Katiyar, Anna Khoreva

We therefore propose to improve the established semantic image synthesis evaluation scheme by analyzing separately the performance of generated images on the biased and unbiased classes for the given segmentation network.

Benchmarking Data Augmentation +1

ResNet After All? Neural ODEs and Their Numerical Solution

1 code implementation30 Jul 2020 Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann

If the trained model is supposed to be a flow generated from an ODE, it should be possible to choose another numerical solver with equal or smaller numerical error without loss of performance.

valid

Grid Saliency for Context Explanations of Semantic Segmentation

2 code implementations NeurIPS 2019 Lukas Hoyer, Mauricio Munoz, Prateek Katiyar, Anna Khoreva, Volker Fischer

Recently, there has been a growing interest in developing saliency methods that provide visual explanations of network predictions.

Image Classification Segmentation +1

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