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Marin Biloš
Marin Biloš
Other namesMarin Bilos
Verified email at in.tum.de
Title
Cited by
Cited by
Year
Intensity-Free Learning of Temporal Point Processes
O Shchur, M Biloš, S Günnemann
International Conference on Learning Representations, 2020
1802020
Lag-llama: Towards foundation models for time series forecasting
K Rasul, A Ashok, AR Williams, A Khorasani, G Adamopoulos, ...
R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Large Foundation …, 2023
842023
Neural flows: Efficient alternative to neural ODEs
M Biloš, J Sommer, SS Rangapuram, T Januschowski, S Günnemann
Advances in neural information processing systems 34, 21325-21337, 2021
702021
Modeling temporal data as continuous functions with stochastic process diffusion
M Biloš, K Rasul, A Schneider, Y Nevmyvaka, S Günnemann
International Conference on Machine Learning, 2452-2470, 2023
53*2023
Uncertainty on asynchronous time event prediction
M Biloš, B Charpentier, S Günnemann
Neural Information Processing Systems, 2019
452019
Lag-llama: Towards foundation models for probabilistic time series forecasting
K Rasul, A Ashok, AR Williams, H Ghonia, R Bhagwatkar, A Khorasani, ...
Preprint, 2024
342024
Fast and flexible temporal point processes with triangular maps
O Shchur, N Gao, M Biloš, S Günnemann
Neural Information Processing Systems, 2020
342020
Scalable Normalizing Flows for Permutation Invariant Densities
M Biloš, S Günnemann
International Conference on Machine Learning, 2021
29*2021
Deep representation learning and clustering of traffic scenarios
N Harmening, M Biloš, S Günnemann
arXiv preprint arXiv:2007.07740, 2020
192020
Add and thin: Diffusion for temporal point processes
D Lüdke, M Biloš, O Shchur, M Lienen, S Günnemann
Advances in Neural Information Processing Systems 36, 56784-56801, 2023
72023
Variational Schr\" odinger Diffusion Models
W Deng, W Luo, Y Tan, M Biloš, Y Chen, Y Nevmyvaka, RTQ Chen
arXiv preprint arXiv:2405.04795, 2024
62024
Lag-llama: Towards foundation models for probabilistic time series forecasting, 2024
K Rasul, A Ashok, AR Williams, H Ghonia, R Bhagwatkar, A Khorasani, ...
URL https://arxiv. org/abs/2310.08278, 0
5
Irregularly-Sampled Time Series Modeling with Spline Networks
M Biloš, E Ramneantu, S Günnemann
arXiv preprint arXiv:2210.10630, 2022
32022
Towards linking social media profiles with user’s WiFi preferred network list
A Dagelić, M Čagalj, T Perković, M Biloš
Ad Hoc Networks 107, 102244, 2020
32020
Recurrent Interpolants for Probabilistic Time Series Prediction
Y Chen, M Biloš, S Mittal, W Deng, K Rasul, A Schneider
arXiv preprint arXiv:2409.11684, 2024
2024
Machine Learning for Irregularly-Sampled Time Series
M Biloš
Technische Universität München, 2024
2024
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Articles 1–16