Search Results for author: Nikolai Kalischek

Found 5 papers, 3 papers with code

BiasBed -- Rigorous Texture Bias Evaluation

1 code implementation23 Nov 2022 Nikolai Kalischek, Rodrigo C. Daudt, Torben Peters, Reinhard Furrer, Jan D. Wegner, Konrad Schindler

With the release of BiasBed, we hope to foster a common understanding of consistent and meaningful comparisons, and consequently faster progress towards learning methods free of texture bias.

Model Selection

Tetrahedral Diffusion Models for 3D Shape Generation

no code implementations23 Nov 2022 Nikolai Kalischek, Torben Peters, Jan D. Wegner, Konrad Schindler

Recently, probabilistic denoising diffusion models (DDMs) have greatly advanced the generative power of neural networks.

3D Shape Generation Denoising +1

Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles

1 code implementation5 Mar 2021 Nico Lang, Nikolai Kalischek, John Armston, Konrad Schindler, Ralph Dubayah, Jan Dirk Wegner

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a key climate mission whose goal is to advance our understanding of the role of forests in the global carbon cycle.

Probabilistic Deep Learning regression

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