15 citations · 16 across the 6 of their papers we have counts for
8 papers
MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training
Lucia Gordon, Serge Belongie, Christian Igel +1
Recent research in geospatial machine learning demonstrates that models pretrained with self-supervised learning on Earth observation data can perform well on downstream tasks with…
SuperF: Neural Implicit Fields for Multi-Image Super-Resolution
Sander Riisøen Jyhne, Christian Igel, Morten Goodwin +3
High-resolution imagery is often hindered by limitations in sensor technology, atmospheric conditions, and costs. Such challenges occur in satellite remote sensing, but also with h…
Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race
Pedram Bakhtiarifard, Pınar Tözün, Christian Igel +1
Sustainability encompasses three key facets: economic, environmental, and social. However, the nascent discourse on sustainable artificial intelligence (AI) predominantly focuses o…
When Can Memorization Improve Fairness?
Bob Pepin, Christian Igel, Raghavendra Selvan
We study to which extent additive fairness metrics (statistical parity, equal opportunity and equalized odds) can be influenced in a multi-class classification problem by memorizin…
BMRS: Bayesian Model Reduction for Structured Pruning
Dustin Wright, Christian Igel, Raghavendra Selvan
Modern neural networks are often massively overparameterized leading to high compute costs during training and at inference. One effective method to improve both the compute and en…
PePR: Performance Per Resource Unit as a Metric to Promote Small-Scale Deep Learning in Medical Image Analysis
Raghavendra Selvan, Bob Pepin, Christian Igel +2
The recent advances in deep learning (DL) have been accelerated by access to large-scale data and compute. These large-scale resources have been used to train progressively larger…
Familiarity-Based Open-Set Recognition Under Adversarial Attacks
Philip Enevoldsen, Christian Gundersen, Nico Lang +2
Open-set recognition (OSR), the identification of novel categories, can be a critical component when deploying classification models in real-world applications. Recent work has sho…
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search
Pedram Bakhtiarifard, Christian Igel, Raghavendra Selvan
Energy consumption from the selection, training, and deployment of deep learning models has seen a significant uptick recently. This work aims to facilitate the design of energy-ef…