Marin Biloš

1. Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
   2023/10/12 by Kashif Rasul, Rasul, Kashif, Arjun Ashok +30 · 45 citations
   Decision Sciences · Computer Science · #Stock Market Forecasting Methods #Time Series Analysis and Forecasting #Forecasting Techniques and Applications
2. Neural Flows: Efficient Alternative to Neural ODEs
   2021/10/25 by Marin Biloš, Johanna Sommer, Biloš, Marin +7 · 18 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
3. Intensity-Free Learning of Temporal Point Processes
   2019/09/26 by Oleksandr Shchur, Shchur, Oleksandr, Marin Biloš +3 · 15 citations
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
4. Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion
   2022/11/04 by Marin Biloš, Biloš, Marin, Kashif Rasul +7 · 4 citations
   Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Time Series Analysis and Forecasting
5. 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
6. Fast and Flexible Temporal Point Processes with Triangular Maps
   2020/06/22 by Oleksandr Shchur, Nicholas Gao, Shchur, Oleksandr +5 · 2 citations
   Computer Science · Engineering · Mathematics · #3D Shape Modeling and Analysis #Computational Geometry and Mesh Generation #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Point processes and geometric inequalities
7. Scalable Normalizing Flows for Permutation Invariant Densities
   2020/10/07 by Marin Biloš, Stephan Günnemann, Biloš, Marin +1 · 1 citation
   Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
8. Variational Schrödinger Diffusion Models
   2024/05/08 by Wei Deng, Deng, Wei, Weijian Luo +10 · 2 citations
   Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Numerical methods in inverse problems #Thermoelastic and Magnetoelastic Phenomena