Marin Bilos

According to our database, Marin Bilos authored at least 16 papers between 2019 and 2024.

Collaborative distances:

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

2024

Machine Learning for Irregularly-Sampled Time Series.

Marin Bilos

PhD thesis, 2024

Recurrent Interpolants for Probabilistic Time Series Prediction.

Yu Chen, Marin Bilos, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider

CoRR, 2024

Variational Schrödinger Diffusion Models.

Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Lag-Llama: Towards Foundation Models for Time Series Forecasting.

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

CoRR, 2023

Add and Thin: Diffusion for Temporal Point Processes.

David Lüdke, Marin Bilos, Oleksandr Shchur, Marten Lienen, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion.

Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann

Proceedings of the International Conference on Machine Learning, 2023

2022

Modeling Temporal Data as Continuous Functions with Process Diffusion.

Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann

CoRR, 2022

Irregularly-Sampled Time Series Modeling with Spline Networks.

Marin Bilos, Emanuel Ramneantu, Stephan Günnemann

CoRR, 2022

2021

Neural Flows: Efficient Alternative to Neural ODEs.

Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Normalizing Flows for Permutation Invariant Densities.

Marin Bilos, Stephan Günnemann

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Equivariant Normalizing Flows for Point Processes and Sets.

Marin Bilos, Stephan Günnemann

CoRR, 2020

Deep Representation Learning and Clustering of Traffic Scenarios.

Nick Harmening, Marin Bilos, Stephan Günnemann

CoRR, 2020

Towards linking social media profiles with user's WiFi preferred network list.

Ante Dagelic, Mario Cagalj, Toni Perkovic, Marin Bilos

Ad Hoc Networks, 2020

Fast and Flexible Temporal Point Processes with Triangular Maps.

Oleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Intensity-Free Learning of Temporal Point Processes.

Oleksandr Shchur, Marin Bilos, Stephan Günnemann

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Uncertainty on Asynchronous Time Event Prediction.

Bertrand Charpentier, Marin Bilos, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019