6 papers
Guided Super-Resolution of Digital Elevation Models with Diffusion-Based Image Generators
Armand Mihai Nicolicioiu, Dominik Narnhofer, Nando Metzger +3
High-resolution digital surface models (DSMs) play an important role in urban analysis, 3D building reconstruction, and infrastructure monitoring, yet their availability remains li…
Panza: Design and Analysis of a Fully-Local Personalized Text Writing Assistant
Armand Nicolicioiu, Eugenia Iofinova, Andrej Jovanovic +6
The availability of powerful open-source large language models (LLMs) opens exciting use-cases, such as using personal data to fine-tune these models to imitate a user's unique wri…
Neural Redshift: Random Networks are not Random Functions
Damien Teney, Armand Nicolicioiu, Valentin Hartmann +1
Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but…
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks
Luca Scimeca, Alexander Rubinstein, Armand Mihai Nicolicioiu +2
Spurious correlations in the data, where multiple cues are predictive of the target labels, often lead to shortcut learning phenomena, where a model may rely on erroneous, easy-to-…
Mitigating Shortcut Learning with Diffusion Counterfactuals and Diverse Ensembles
Luca Scimeca, Alexander Rubinstein, Damien Teney +2
Spurious correlations in the data, where multiple cues are predictive of the target labels, often lead to a phenomenon known as shortcut learning, where a model relies on erroneous…
ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results
Nina Miolane, Matteo Caorsi, Umberto Lupo +30
This paper presents the computational challenge on differential geometry and topology that happened within the ICLR 2021 workshop "Geometric and Topological Representation Learning…