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research.qmd
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---
title: "Research"
---
## Selected Publications
1. V. Kostić, K. Lounici, H. Halconruy, T. Devergne and M. Pontil. **Learning the Infinitesimal Generator of Stochastic Diffusion Processes**. *Advances in Neural Information Processing Systems 37* (NeurIPS2024)
2. T. Devergne, V. Kostić, M. Parrinello and M. Pontil. **From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach**. *Advances in Neural Information Processing Systems 37* (NeurIPS2024)
3. V. Kostić, K. Lounici, G. Pacreau, P. Novelli, G. Turri and M. Pontil. **Neural Conditional Probability for Inference**. *Advances in Neural Information Processing Systems 37* (NeurIPS2024)
4. V. Kostić, P. Inzerili, K. Lounici, P. Novelli and M. Pontil. **Consistent Long-Term Forecasting of Ergodic Dynamical Systems**. *41st International Conference on Machine Learning* (ICML 2024)
5. V.R. Kostic, P. Novelli, R. Grazzi and K. Lounici. **Learning Invariant Representations of Time-Homogeneous Stochastic Dynamical Systems**. *Twelfth International Conference on Learning Representations* (ICLR 2024)
6. V. R. Kostic, P. Novelli, A. Maurer, C. Ciliberto, L. Rosasco and M. Pontil. **Learning dynamical systems via Koopman operator regression in reproducing kernel Hilbert spaces**. *Advances in Neural Information Processing Systems 35* (NeurIPS2022)
7. V. Kostić and S. Salzo. **Randomized Bregman Projections for Stochastic Feasibility Problems**. *Numerical Algorithms* 93(3), pp. 1269-1307 (2022)
8. V. Kostić, L. Cvetković, E. Šanca. **From Pseudospectra of Diagonal Blocks to Pseudospectrum of a Full Matrix**. *Journal of Computational and Applied Mathematics*, Vol 386, online 113265 (2020)
9. V. Kostić and D. Gardašević. **On the Geršgorin-type Localizations for Nonlinear Eigenvalue Problems**. *Applied Mathematics and Computation*, Vol. 337, No 1, pp. 179-189 (2018)
10. V. Kostić, Lj. Cvetković and D. Lj. Cvetković, **Pseudospectra localizations and their applications**,
*Numerical Linear Algebra with Applications* Vol 23 (2), pp. 356–372 (2016)
## Selected talks
1. [**Learning Representations of Markov Processes**](papers/RepresentationLearing_2024.pdf) at *IEEE Conference on Decision and Control*, Milano, Italy (2024)
2. [**Consistent Long-Term Forecasting of geometrically ergodic dynamical systems**](papers/Porquerolles_2024.pdf) at at *New Trends in Statistical Learning IV*, Porquerolles, France (2024)
3. [**Koopman Operator Regression: Statistical Learning Perspective to Data-driven Dynamical Systems**](papers/Porquerolles%202023.pdf) at *New Trends in Statistical Learning III*, Porquerolles, France (2023)
4. [**Sharp Spectral Rates for Koopman Operator Learning**](papers/NeurIPS2023_SpectralRates_VK.pdf) at *Conference on Neural Information Processing Systems*, New Orleans, USA (2023)
5. [**M -matrices as a tool for spectral and pseudospectral analysis**](papers/VKostic_NASC2019_talk.pdf) at *Conference on Numerical Linear Algebra and Scientific Computing*, Nanjing, China (2019)
6. [**Matrix nearness problems for Lyapunov-type stability domains: computing Distance-to-Delocalization**](papers/VKostic_SIAM_LA15_talk.pdf) at *SIAM Conference on Applied Linear Algebra*, Atlanta, USA (2015)