3 papers
cs.LG2026
Federated Learning with Energy-Based Structured Probabilistic Inference
Dario Fenoglio, Daniil Kirilenko, Martin Gjoreski +1
Federated learning typically aggregates client updates using fixed or heuristic weighting rules, which can be suboptimal when clients have heterogeneous data and varying contributi…
cs.AI2026
Concept-based Visual Counterfactual Explanations with Diffusion Models
Yassine Oueslati, Daniil Kirilenko, Martin Gjoreski +1
Visual counterfactual explanations aim to answer "what minimal change to this image would flip the model's prediction?", and are increasingly important as vision models are deploye…
cs.LG2024
Object-Centric Learning with Slot Mixture Module
Daniil Kirilenko, Vitaliy Vorobyov, Alexey K. Kovalev +1
Object-centric architectures usually apply a differentiable module to the entire feature map to decompose it into sets of entity representations called slots. Some of these methods…