Multimodal Meta-Learning for Time Series Regression. - Sebastian Pineda-Arango; Felix Heinrich; Kiran Madhusudhanan; Lars Schmidt-Thieme (AALTD@ECML/PKDD, 2021)

Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. - Kiran Madhusudhanan; Johannes Burchert; Nghia Duong-Trung; Stefan Born; Lars Schmidt-Thieme (CoRR, 2021)

U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. - Kiran Madhusudhanan; Johannes Burchert; Nghia Duong-Trung; Stefan Born; Lars Schmidt-Thieme (ECML/PKDD (6), 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)

Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series. - Nghia Duong-Trung; Stefan Born; Kiran Madhusudhanan; Randolf Scholz; Johannes Burchert; Danh Le Phuoc; Lars Schmidt-Thieme (CoRR, 2022)

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

ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. - Kiran Madhusudhanan; Gunnar Behrens; Maximilian Stubbemann; Lars Schmidt-Thieme (IEEE Big Data, 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)

Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting. - Vijaya Krishna Yalavarthi; Randolf Scholz; Kiran Madhusudhanan; Stefan Born; Lars Schmidt-Thieme (CoRR, 2024)

Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting. - Dona Arabi; Jafar Bakhshaliyev; Ayse Coskuner; Kiran Madhusudhanan; Kami Serdar Uckardes (CoRR, 2024)

Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting? - Ibram Abdelmalak; Kiran Madhusudhanan; Jungmin Choi; Maximilian Stubbemann; Lars Schmidt-Thieme (CoRR, 2025)