17 citations · 19 across the 6 of their papers we have counts for
6 papers
Hyperparameter Optimization via Interacting with Probabilistic Circuits
Jonas Seng, Fabrizio Ventola, Zhongjie Yu +1
Despite the growing interest in designing truly interactive hyperparameter optimization (HPO) methods, to date, only a few allow to include human feedback. Existing interactive Bay…
Probabilistic Circuits That Know What They Don't Know
Fabrizio Ventola, Steven Braun, Zhongjie Yu +2
Probabilistic circuits (PCs) are models that allow exact and tractable probabilistic inference. In contrast to neural networks, they are often assumed to be well-calibrated and rob…
DAFNe: A One-Stage Anchor-Free Approach for Oriented Object Detection
Steven Lang, Fabrizio Ventola, Kristian Kersting
We present DAFNe, a Dense one-stage Anchor-Free deep Network for oriented object detection. As a one-stage model, it performs bounding box predictions on a dense grid over the inpu…
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
Nils Thoma, Zhongjie Yu, Fabrizio Ventola +1
Time series forecasting is a relevant task that is performed in several real-world scenarios such as product sales analysis and prediction of energy demand. Given their accuracy pe…
User-Level Label Leakage from Gradients in Federated Learning
Aidmar Wainakh, Fabrizio Ventola, Till Müßig +6
Federated learning enables multiple users to build a joint model by sharing their model updates (gradients), while their raw data remains local on their devices. In contrast to the…
Random Sum-Product Forests with Residual Links
Fabrizio Ventola, Karl Stelzner, Alejandro Molina +1
Tractable yet expressive density estimators are a key building block of probabilistic machine learning. While sum-product networks (SPNs) offer attractive inference capabilities, o…