Biloš, Marin

1. Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
   2023/10/12 by Kashif Rasul, Arjun Ashok, Rasul, Kashif +30 · 39 citations
   Decision Sciences · Computer Science · #Stock Market Forecasting Methods #Time Series Analysis and Forecasting #Forecasting Techniques and Applications
2. Intensity-Free Learning of Temporal Point Processes
   2019/09/26 by Shchur, Oleksandr, Biloš, Marin, Günnemann, Stephan · 14 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Neural Flows: Efficient Alternative to Neural ODEs
   2021/10/25 by Marin Biloš, Johanna Sommer, Biloš, Marin +7 · 16 citations
   Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Numerical Analysis (math.NA) #Stock Market Forecasting Methods
4. Add and Thin: Diffusion for Temporal Point Processes
   2023/11/02 by David Lüdke, Marin Biloš, Lüdke, David +7 · 5 citations
   Mathematics · #Point processes and geometric inequalities
5. Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion
   2022/11/04 by Biloš, Marin, Rasul, Kashif, Schneider, Anderson +2 · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
6. Scalable Normalizing Flows for Permutation Invariant Densities
   2020/10/07 by Biloš, Marin, Günnemann, Stephan · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Fast and Flexible Temporal Point Processes with Triangular Maps
   2020/06/22 by Shchur, Oleksandr, Gao, Nicholas, Biloš, Marin +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
8. Variational Schrödinger Diffusion Models
   2024/05/08 by Wei Deng, Deng, Wei, Weijian Luo +10 · 1 citation
   Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Numerical methods in inverse problems #Thermoelastic and Magnetoelastic Phenomena