Feofanov, Vasilii

12 publications

ICML 2025 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

ICLRW 2025 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

TMLR 2025 Leveraging Gradients for Unsupervised Accuracy Estimation Under Distribution Shift Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko, Jianfeng Zhang, Bo An

NeurIPS 2024 Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko

NeurIPSW 2024 Enhancing Multivariate Time Series Forecasting via Multi-Task Learning and Random Matrix Theory Romain Ilbert, Malik Tiomoko, Cosme Louart, Vasilii Feofanov, Themis Palpanas, Ievgen Redko

AISTATS 2024 Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko

NeurIPS 2024 MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Weijian Deng, Jianfeng Zhang, Bo An

NeurIPSW 2024 Measuring Pre-Training Data Quality Without Labels for Time Series Foundation Models Songkang Wen, Vasilii Feofanov, Jianfeng Zhang

JMLR 2024 Multi-Class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

ICML 2024 SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

ICML 2023 Random Matrix Analysis to Balance Between Supervised and Unsupervised Learning Under the Low Density Separation Assumption Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux

AAAI 2019 Transductive Bounds for the Multi-Class Majority Vote Classifier Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini