Tavallali, Peyman
- Darcy, Matthieu and Hamzi, Boumediene, et el. (2023) One-shot learning of stochastic differential equations with data adapted kernels; Physica D; Vol. 444; Art. No. 133583; 10.1016/j.physd.2022.133583
- Hamze Bajgiran, Hamed and Batlle Franch, Pau, et el. (2022) Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball; 10.48550/arXiv.2108.10517
- Tavallali, Peyman and Hamze Bajgiran, Hamed, et el. (2021) Decision Theoretic Bootstrapping; 10.48550/arXiv.2103.09982
- Su, Hui and Wu, Longtao, et el. (2020) Applying Satellite Observations of Tropical Cyclone Internal Structures to Rapid Intensification Forecast With Machine Learning; Geophysical Research Letters; Vol. 47; No. 17; Art. No. e2020GL089102; 10.1029/2020gl089102
- Tavallali, Peyman and Koorehdavoudi, Hana, et el. (2018) Intrinsic Frequency Analysis and Fast Algorithms; Scientific Reports; Vol. 8; Art. No. 4858; PMCID PMC5861104; 10.1038/s41598-018-22907-4
- Tavallali, Peyman and Hou, Thomas Y., et el. (2015) On the convergence and accuracy of the cardiovascular intrinsic frequency method; Royal Society Open Science; Vol. 2; No. 12; Art. No. 150475; PMCID PMC4807454; 10.1098/rsos.150475
- Petrasek, Danny and Pahlevan, Niema M., et el. (2015) Intrinsic Frequency and the Single Wave Biopsy: Implications for Insulin Resistance; Journal of Diabetes Science and Technology; Vol. 9; No. 6; 1246-1252; PMCID PMC4667296; 10.1177/1932296815588108