Johannes Burchert

According to our database, Johannes Burchert authored at least 15 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting.

Jafar Bakhshaliyev, Johannes Burchert, Niels Landwehr, Lars Schmidt-Thieme

CoRR, April, 2026

LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification.

Johannes Burchert, Ahmad Bdeir, Tom Hanika, Lars Schmidt-Thieme, Niels Landwehr

CoRR, March, 2026

2025

Robust Hyperbolic Learning with Curvature-Aware Optimization.

Ahmad Bdeir, Johannes Burchert, Lars Schmidt-Thieme, Niels Landwehr

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training.

Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme

CoRR, 2024

A Cross-Domain Benchmark for Active Learning.

Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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

ConvMix: Combining Intermediate Latent Features in Deep Convolutional Neural Networks.

Mofassir ul Islam Arif, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the IEEE International Conference on Big Data, 2023

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

Tripletformer for Probabilistic Interpolation of Asynchronous Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

CoRR, 2022

U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting.

Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Few-Shot Forecasting of Time-Series with Heterogeneous Channels.

Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

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