Kiran Madhusudhanan

18 papers A* 1A 1B 2Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Channel Dependence, Limited Lookback Windows, and the Simplicity of Datasets: How Biased is Time Series Forecasting? CoRR Ibram Abdelmalak, Kiran Madhusudhanan, Jungmin Choi, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	A	`conf`	TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression. ECAI Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Jonas Sonntag, Maximilian Stubbemann, Lars Schmidt-Thieme
2025	J	`jnl`	TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression. CoRR Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Jonas Sonntag, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	A*	`conf`	GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. AAAI Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme
2024	—	`conf`	Hyperparameter Tuning MLP's for Probabilistic Time Series Forecasting. PAKDD (6) Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
2024	J	`jnl`	Hyperparameter Tuning MLPs for Probabilistic Time Series Forecasting. CoRR Kiran Madhusudhanan, Shayan Jawed, Lars Schmidt-Thieme
2024	J	`jnl`	Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting. CoRR Vijaya Krishna Yalavarthi, Randolf Scholz, Kiran Madhusudhanan, Stefan Born, Lars Schmidt-Thieme
2024	B	`conf`	ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. IEEE Big Data Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing. CoRR Kiran Madhusudhanan, Gunnar Behrens, Maximilian Stubbemann, Lars Schmidt-Thieme
2024	J	`jnl`	Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting. CoRR Dona Arabi, Jafar Bakhshaliyev, Ayse Coskuner, Kiran Madhusudhanan, Kami Serdar Uckardes
2023	B	`conf`	Forecasting Early with Meta Learning. IJCNN Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2023	J	`jnl`	Forecasting Early with Meta Learning. CoRR Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme
2022	J	`jnl`	A.I. and Data-Driven Mobility at Volkswagen Financial Services AG. CoRR 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
2022	J	`jnl`	Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series. CoRR Nghia Duong-Trung, Stefan Born, Kiran Madhusudhanan, Randolf Scholz, Johannes Burchert, Danh Le Phuoc, Lars Schmidt-Thieme
2022	—	`conf`	U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. ECML/PKDD (6) Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme
2021	—	`conf`	Multimodal Meta-Learning for Time Series Regression. AALTD@ECML/PKDD Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
2021	J	`jnl`	Multimodal Meta-Learning for Time Series Regression. CoRR Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme
2021	J	`jnl`	Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. CoRR Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme