278 citations · 832 across the 38 of their papers we have counts for
41 papers
Breeding Programs Optimization with Reinforcement Learning
Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis +3
Crop breeding is crucial in improving agricultural productivity while potentially decreasing land usage, greenhouse gas emissions, and water consumption. However, breeding programs…
Hypernetwork-Driven Model Fusion for Federated Domain Generalization
Marc Bartholet, Taehyeon Kim, Ami Beuret +2
Federated Learning (FL) faces significant challenges with domain shifts in heterogeneous data, degrading performance. Traditional domain generalization aims to learn domain-invaria…
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective
João B. S. Carvalho, Mengtao Zhang, Robin Geyer +2
Anomaly detection (AD) is the machine learning task of identifying highly discrepant abnormal samples by solely relying on the consistency of the normal training samples. Under the…
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings
Lukas Klein, João B. S. Carvalho, Mennatallah El-Assady +3
Explainable AI aims to render model behavior understandable by humans, which can be seen as an intermediate step in extracting causal relations from correlative patterns. Due to th…
Explore In-Context Learning for 3D Point Cloud Understanding
Zhongbin Fang, Xiangtai Li, Xia Li +3
With the rise of large-scale models trained on broad data, in-context learning has become a new learning paradigm that has demonstrated significant potential in natural language pr…
How to Enable Uncertainty Estimation in Proximal Policy Optimization
Eugene Bykovets, Yannick Metz, Mennatallah El-Assady +2
While deep reinforcement learning (RL) agents have showcased strong results across many domains, a major concern is their inherent opaqueness and the safety of such systems in real…