Tal El-Hay  Tal El-Hay photo         

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Research Staff Member



Comment: Causal Inference Competitions: Where Should We Aim?
Ehud Karavani, Tal El-hay, Yishai Shimoni, Chen Yanover
Statistical Science34, 86-89, 2019

How the weather affects the pain of citizen scientists using a smartphone app
William G. Dixon, Anna L. Beukenhorst, Belay B. Yimer, Louise Cook, Antonio Gasparrini, Tal El-Hay, Bruce Hellman, Ben James, Ana M. Vicedo-Cabrera, Malcolm Maclure, Ricardo Silva, John Ainsworth, Huai Leng Pisaniello, Thomas House, Mark Lunt, Carolyn Gamble, Caroline Sanders, David M. Schultz, Jamie C. Sergeant, John McBeth
npj Digital Medicine 2(1), 105, 2019


Factorial HMMs with Collapsed Gibbs Sampling for Optimizing Long-term HIV Therapy
Amit Gruber, Chen Yanover, Tal El-Hay, Anders Sonnerborg, Vanni Borghi, Francesca Incardona, Yaara Goldschmidt
International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 317--326, 2018

Characterizing Subpopulations with Better Response to Treatment Using Observational Data-an Epilepsy Case Study
Ozery-Flato, Michal and El-Hay, Tal and Aharonov, Ranit and Parush-Shear-Yashuv, Naama and Goldschmidt, Yaara and Borghs, Simon and Chan, Jane and Haddad, Nassim and Pierre-Louis, Bosny and Kalilani, Linda
bioRxiv, 290585, Cold Spring Harbor Laboratory, 2018


Integrated multisystem analysis in a mental health and criminal justice ecosystem
Erin Falconer, Tal El-Hay, Dimitris Alevras, John P Docherty, Chen Yanover, Alan Kalton, Yaara Goldschmidt, Michal Rosen-Zvi
Health & Justice, 2017


Paradoxical Hypersusceptibility of Drug-Resistant M. tuberculosis to Beta-Lactam Antibiotics
Keira A Cohen*, Tal El-Hay*, Kelly L Wyres*, Omer Weissbrod, Vanisha Munsamy, Chen Yanover, Ranit Aharonov, Oded Shaham, Thomas C Conway, Yaara Goldschmidt, William R Bishai, Alexander S Pym
EBioMedicine, Elsevier, 2016


Integrated Multisystem Analysis in a Mental Health and Criminal Justice Ecosystem
Erin Falconer, Tal El-Hay, Dimitris Alevras, John Docherty, Chen Yanover, Alan Kalton, Yaara Goldschmidt, Michal Rosen-Zvi
AMIA Annual Symposium Proceedings, pp. 526, 2014

Structured Proportional Jump Processes
Tal El-Hay, Omer Weissbrod, Elad Eban, Maurizio Zazzi, Francesca Incardona
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI), 2014


Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome
Michal Ozery-Flato, Naama Parush, Tal El-Hay, Zydrune Visockiene, Ligita Rylivskyte, Jolita Badariene, Svetlana Solovjova, Milda Kovaite, Rokas Navickas, Aleksandras Laucevicius
Diabetology \& metabolic syndrome 5(1), 36, BioMed Central Ltd, 2013


Information-based sequential selection of clinical tests in risk assessment
N. Parush, T. El-Hay, M. Ozery-Flato, L. Ryliskyte, Z. Visockiene, A. Laucevicius
Stud Health Technol Inform180, 781--785, 2012


Mean Field Variational Approximation for Continuous-Time Bayesian Networks
I Cohn*, T El-Hay*, N Friedman, R Kupferman
Journal of Machine Learning Research 11(Oct), 2745, 2010

Continuous-Time Belief Propagation
T El-Hay, I Cohn, N Friedman, R Kupferman
Proc. Twenty Seventh International Conf. on Machine Learning (ICML), 2010


Mean field variational approximation for continuous-time Bayesian networks
I Cohn, T El-Hay, N Friedman, R Kupferman
Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, pp. 91--100, 2009


Gibbs sampling in factorized continuous-time Markov processes
T El-Hay, N Friedman, R Kupferman
Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence, pp. 169--178, 2008


Continuous time markov networks
T El-Hay, N Friedman, D Koller, R Kupferman
Proceedings of the Twenty-second Conference on Uncertainty in Artificial Intelligence, 2006


Incorporating expressive graphical models in variational approximations: Chain-graphs and hidden variables
T El-Hay, N Friedman
Proceedings of the Eighteenth Conference in Artificial Intelligence, 2001