Multi-step Forecasting via Multi-task Learning. - Shayan Jawed; Ahmed Rashed; Lars Schmidt-Thieme (IEEE BigData, 2019)

A Deep Multi-task Approach for Residual Value Forecasting. - Ahmed Rashed; Shayan Jawed; Jens Rehberg; Josif Grabocka; Lars Schmidt-Thieme; Andre Hintsches (ECML/PKDD (3), 2019)

Data-Driven Vehicle Trajectory Forecasting. - Shayan Jawed; Eya Boumaiza; Josif Grabocka; Lars Schmidt-Thieme (CoRR, 2019)

Optimal Topology Search for Fast Model Averaging in Decentralized Parallel SGD. - Mohsan Jameel; Shayan Jawed; Lars Schmidt-Thieme (PAKDD (2), 2020)

Self-supervised Learning for Semi-supervised Time Series Classification. - Shayan Jawed; Josif Grabocka; Lars Schmidt-Thieme (PAKDD (1), 2020)

MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems. - Ahmed Rashed; Shayan Jawed; Lars Schmidt-Thieme; Andre Hintsches (RecSys, 2020)

Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets. - Shayan Jawed; Hadi S. Jomaa; Lars Schmidt-Thieme; Josif Grabocka (ECML/PKDD (1), 2021)

GQFormer: A Multi-Quantile Generative Transformer for Time Series Forecasting. - Shayan Jawed; Lars Schmidt-Thieme (IEEE Big Data, 2022)

A.I. and Data-Driven Mobility at Volkswagen Financial Services AG. - Shayan Jawed; Mofassir ul Islam Arif; Ahmed Rashed; Kiran Madhusudhanan; Shereen Elsayed; Mohsan Jameel; Alexei Volk; Andre Hintsches; Marlies Kornfeld; Katrin Lange; Lars Schmidt-Thieme (CoRR, 2022)

Auxiliary Quantile Forecasting with Linear Networks. - Shayan Jawed; Lars Schmidt-Thieme (CoRR, 2022)

Pricing Used Vehicles at Volkswagen Financial Services AG. - Shayan Jawed; Jan Stening; Lars Schmidt-Thieme (IEEE Big Data, 2023)

Forecasting Early with Meta Learning. - Shayan Jawed; Kiran Madhusudhanan; Vijaya Krishna Yalavarthi; Lars Schmidt-Thieme (IJCNN, 2023)

Forecasting Irregularly Sampled Time Series using Graphs. - Vijaya Krishna Yalavarthi; Kiran Madusudanan; Randolf Scholz; Nourhan Ahmed; Johannes Burchert; Shayan Jawed; Stefan Born; Lars Schmidt-Thieme (CoRR, 2023)

GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. - Vijaya Krishna Yalavarthi; Kiran Madhusudhanan; Randolf Scholz; Nourhan Ahmed; Johannes Burchert; Shayan Jawed; Stefan Born; Lars Schmidt-Thieme (AAAI, 2024)

Hyperparameter Tuning MLP's for Probabilistic Time Series Forecasting. - Kiran Madhusudhanan; Shayan Jawed; Lars Schmidt-Thieme (PAKDD (6), 2024)

Hyperparameter Tuning MLPs for Probabilistic Time Series Forecasting. - Kiran Madhusudhanan; Shayan Jawed; Lars Schmidt-Thieme (CoRR, 2024)