Michael Riedl's Blog - Dabbling in all things.
M. Riedl, S. Mukherjee, and M. Gauthier, "Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma," in Molecular Pharmaceutics Article ASAP, Sept. 2023. doi: 10.1021/acs.molpharmaceut.3c00129
M. Riedl and L. C. Potter, "Multimodel Shrinkage for Knowledge-Aided Space-Time Adaptive Processing," in IEEE Transactions on Aerospace and Electronic Systems, vol. 54, no. 5, pp. 2601-2610, Oct. 2018. doi: 10.1109/TAES.2018.2813898
M. Riedl and L. C. Potter, "Knowledge-Aided Bayesian Space-Time Adaptive Processing," in IEEE Transactions on Aerospace and Electronic Systems, vol. 54, no. 4, pp. 1850-1861, Aug. 2018. doi: 10.1109/TAES.2018.2805141
M. Riedl, L. Potter, C. Bryant and E. Ertin, "Joint Synthetic Aperture Radar and Space-Time Adaptive Processing on a Single Receive Channel," in IEEE Transactions on Aerospace and Electronic Systems, vol. 51, no. 1, pp. 331-341, January 2015. doi: 10.1109/TAES.2014.130596
S. Hosseini, R. Larson, P. Shokouhi, V. Kumar, S. Prathipati, D. Kifer, J. Garcez, L. Ayala, M. Riedl, B. Hill, and S. Tamrakar, Reservoir Modeling Using Fast Predictive Machine Learning Algorithms for Geological Carbon Storage. In Machine Learning Applications in Subsurface Energy Resource Management (pp. 233-250). CRC Press.
P. Alexander, M. Gauthier, S. Deforte, J. Geppert, J. Ramirez, M. Riedl, J. Bickel, L. Sleeper, R. R. Thiagarajan, S. Dufek, W. White, and K. J. Jenkins. “AI-Enabled Prediction of Bleeding in Children Supported with Extracorporeal Membrane Oxygenation.” 72nd Annual Scientific Session of the American College of Cardiology, March 2023.
M. Riedl and S. Mukherjee. “Deep Learning QSAR Modeling for Fraction Unbound in Human Plasma.” In: The Toxicologist: Supplement to Toxicological Sciences, Volume 186 (Issue S1), Society of Toxicology, 2022. Abstract no. 4672
S. Mawalkar, P. Ravi Ganesh, J. Schuetter, M. Riedl, and S. Mishra. “Predictive Analysis of Pressure and Temperature in Carbonate Reservoirs.” 16th International Conference on Greenhouse Gas Control Technologies GHGT-16, August 2022. http://dx.doi.org/10.2139/ssrn.4283017
P. Alexander, S. DeForte, S. Dufek, M. Gauthier, J. Geppert, J. Ramirez, M. Riedl, W. White, J. Bickel, A. Nemati Hayati, L. Sleeper, R. Thiagarajan and K. J. Jenkins. "AI-Enabled Prediction of Bleeding in Patients Supported on Extracorporeal Membrane Oxygenation." Circulation 146.Suppl_1 (2022): A15673-A15673.
M. Riedl and L. C. Potter "Knowledge-aided GMTI in a Bayesian framework", Proc. SPIE 9475, Algorithms for Synthetic Aperture Radar Imagery XXII, 947506 (13 May 2015); https://doi.org/10.1117/12.2181907
M. Riedl and L. C. Potter, "Knowledge-aided GMTI in a Bayesian framework," 2015 IEEE Radar Conference (RadarCon), Arlington, VA, USA, 2015, pp. 1240-1243, doi: 10.1109/RADAR.2015.7131184.
M. Riedl, L. C. Potter, and E. Ertin "Augmenting synthetic aperture radar with space time adaptive processing", Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, 87460D (23 May 2013); https://doi.org/10.1117/12.2019075