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ORCIDMarin Bilos
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2020 – today
- 2024
[b1]Marin Bilos:
Machine Learning for Irregularly-Sampled Time Series. Technical University of Munich, Germany, 2024- [c8]Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen:
Variational Schrödinger Diffusion Models. ICML 2024 - [i12]Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen:
Variational Schrödinger Diffusion Models. CoRR abs/2405.04795 (2024) - [i11]Yu Chen, Marin Bilos, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider:
Recurrent Interpolants for Probabilistic Time Series Prediction. CoRR abs/2409.11684 (2024) - 2023
- [c7]Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann:
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion. ICML 2023: 2452-2470 - [c6]David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann:
Add and Thin: Diffusion for Temporal Point Processes. NeurIPS 2023 - [i10]Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Marin Bilos, Hena Ghonia, Nadhir Vincent Hassen, Anderson Schneider, Sahil Garg, Alexandre Drouin, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish:
Lag-Llama: Towards Foundation Models for Time Series Forecasting. CoRR abs/2310.08278 (2023) - [i9]David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann:
Add and Thin: Diffusion for Temporal Point Processes. CoRR abs/2311.01139 (2023) - 2022
- [i8]Marin Bilos, Emanuel Ramneantu, Stephan Günnemann:
Irregularly-Sampled Time Series Modeling with Spline Networks. CoRR abs/2210.10630 (2022) - [i7]Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann:
Modeling Temporal Data as Continuous Functions with Process Diffusion. CoRR abs/2211.02590 (2022) - 2021
- [c5]Marin Bilos, Stephan Günnemann:
Scalable Normalizing Flows for Permutation Invariant Densities. ICML 2021: 957-967 - [c4]Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann:
Neural Flows: Efficient Alternative to Neural ODEs. NeurIPS 2021: 21325-21337 - [i6]Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann:
Neural Flows: Efficient Alternative to Neural ODEs. CoRR abs/2110.13040 (2021) - 2020
- [j1]Ante Dagelic, Mario Cagalj, Toni Perkovic
, Marin Bilos:
Towards linking social media profiles with user's WiFi preferred network list. Ad Hoc Networks 107: 102244 (2020) - [c3]Oleksandr Shchur, Marin Bilos, Stephan Günnemann:
Intensity-Free Learning of Temporal Point Processes. ICLR 2020 - [c2]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. NeurIPS 2020 - [i5]Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann:
Fast and Flexible Temporal Point Processes with Triangular Maps. CoRR abs/2006.12631 (2020) - [i4]Nick Harmening, Marin Bilos, Stephan Günnemann:
Deep Representation Learning and Clustering of Traffic Scenarios. CoRR abs/2007.07740 (2020) - [i3]Marin Bilos, Stephan Günnemann:
Equivariant Normalizing Flows for Point Processes and Sets. CoRR abs/2010.03242 (2020)
2010 – 2019
- 2019
- [c1]Bertrand Charpentier, Marin Bilos, Stephan Günnemann:
Uncertainty on Asynchronous Time Event Prediction. NeurIPS 2019: 12831-12840 - [i2]Oleksandr Shchur, Marin Bilos, Stephan Günnemann:
Intensity-Free Learning of Temporal Point Processes. CoRR abs/1909.12127 (2019) - [i1]Marin Bilos, Bertrand Charpentier, Stephan Günnemann:
Uncertainty on Asynchronous Time Event Prediction. CoRR abs/1911.05503 (2019)
Coauthor Index
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