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Johannes Burchert
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2020 – today
- 2024
- [c6]Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme:
GraFITi: Graphs for Forecasting Irregularly Sampled Time Series. AAAI 2024: 16255-16263 - [i9]Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme:
Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training. CoRR abs/2404.06966 (2024) - [i8]Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme:
A Cross-Domain Benchmark for Active Learning. CoRR abs/2408.00426 (2024) - 2023
- [c5]Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme:
Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series. IEEE Big Data 2023: 986-995 - [c4]Mofassir ul Islam Arif, Johannes Burchert, Lars Schmidt-Thieme:
ConvMix: Combining Intermediate Latent Features in Deep Convolutional Neural Networks. SCIA (2) 2023: 156-174 - [i7]Vijaya Krishna Yalavarthi, Kiran Madusudanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme:
Forecasting Irregularly Sampled Time Series using Graphs. CoRR abs/2305.12932 (2023) - [i6]Thorben Werner, Johannes Burchert, Lars Schmidt-Thieme:
Towards Comparable Active Learning. CoRR abs/2311.18356 (2023) - 2022
- [c3]Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme:
DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. DSAA 2022: 1-10 - [c2]Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme:
Few-Shot Forecasting of Time-Series with Heterogeneous Channels. ECML/PKDD (6) 2022: 3-18 - [c1]Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme:
U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. ECML/PKDD (6) 2022: 36-52 - [i5]Lukas Brinkmeyer, Rafael Rêgo Drumond, Johannes Burchert, Lars Schmidt-Thieme:
Few-Shot Forecasting of Time-Series with Heterogeneous Channels. CoRR abs/2204.03456 (2022) - [i4]Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme:
DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series. CoRR abs/2208.11374 (2022) - [i3]Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme:
Tripletformer for Probabilistic Interpolation of Asynchronous Time Series. CoRR abs/2210.02091 (2022) - [i2]Nghia Duong-Trung, Stefan Born, Kiran Madhusudhanan, Randolf Scholz, Johannes Burchert, Danh Le Phuoc, Lars Schmidt-Thieme:
Put Attention to Temporal Saliency Patterns of Multi-Horizon Time Series. CoRR abs/2212.07771 (2022) - 2021
- [i1]Kiran Madhusudhanan, Johannes Burchert, Nghia Duong-Trung, Stefan Born, Lars Schmidt-Thieme:
Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting. CoRR abs/2110.08255 (2021)
Coauthor Index
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last updated on 2024-09-09 00:17 CEST by the dblp team
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