2 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
ePC: Fast and Deep Predictive Coding in Digital Simulation
Cédric Goemaere, Gaspard Oliviers, Rafal Bogacz +1
Predictive Coding (PC) offers a brain-inspired alternative to backpropagation for neural network training, described as a physical system minimizing its internal energy. However, i…
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
Karel D'Oosterlinck, Winnie Xu, Chris Develder +5
Large Language Models (LLMs) are often aligned using contrastive alignment objectives and preference pair datasets. The interaction between model, paired data, and objective makes…
Accelerating Hopfield Network Dynamics: Beyond Synchronous Updates and Forward Euler
Cédric Goemaere, Johannes Deleu, Thomas Demeester
The Hopfield network serves as a fundamental energy-based model in machine learning, capturing memory retrieval dynamics through an ordinary differential equation (ODE). The model'…
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data
Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey +4
Recent advances in generative models facilitate the creation of synthetic data to be made available for research in privacy-sensitive contexts. However, the analysis of synthetic d…