activity
20212025
most citedStable Training of Probabilistic Models Using the Leave-One-Out Maximum Log-Likelihood Objective

2 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

stat.AP2025

The Living Forecast: Evolving Day-Ahead Predictions into Intraday Reality

Kutay Bölat, Peter Palensky, Simon Tindemans

Accurate intraday forecasts are essential for power system operations, complementing day-ahead forecasts that gradually lose relevance as new information becomes available. This pa…

cs.LG2025

Clustering Rooftop PV Systems via Probabilistic Embeddings

Kutay Bölat, Tarek Alskaif, Peter Palensky +1

As the number of rooftop photovoltaic (PV) installations increases, aggregators and system operators are required to monitor and analyze these systems, raising the challenge of int…

cs.LG2025

Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders

Konrad Sundsgaard, Kutay Bölat, Guangya Yang

Electricity distribution cable networks suffer from incomplete and unbalanced data, hindering the effectiveness of machine learning models for predictive maintenance and reliabilit…

cs.LG2025

One Model to Forecast Them All and in Entity Distributions Bind Them

Kutay Bölat, Simon Tindemans

Probabilistic forecasting in power systems often involves multi-entity datasets like households, feeders, and wind turbines, where generating reliable entity-specific forecasts pre…

cs.LG2024

GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries

Kutay Bölat, Simon Tindemans

Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires employing user information, and conve…

stat.ML2023★ 2 cited

Stable Training of Probabilistic Models Using the Leave-One-Out Maximum Log-Likelihood Objective

Kutay Bölat, Simon H. Tindemans, Peter Palensky

Probabilistic modelling of power systems operation and planning processes depends on data-driven methods, which require sufficiently large datasets. When historical data lacks this…

eess.SP2021

Channel State Information Based Localization with Deep Learning

Kutay Bölat

Localization is one of the most important problems in various fields such as robotics and wireless communications. For instance, Unmanned Aerial Vehicles (UAVs) require the informa…