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Robert J. Webber
Researcher at Courant Institute of Mathematical Sciences
Publications - 42
Citations - 320
Robert J. Webber is an academic researcher from Courant Institute of Mathematical Sciences. The author has contributed to research in topics: Computer science & Quantum Monte Carlo. The author has an hindex of 9, co-authored 29 publications receiving 199 citations. Previous affiliations of Robert J. Webber include University of Chicago & New York University.
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Project ASPIRE: Spoken Language Intervention Curriculum for Parents of Low-socioeconomic Status and Their Deaf and Hard-of-Hearing Children.
Dana L. Suskind,Eileen Graf,Kristin R. Leffel,Marc W. Hernandez,Elizabeth Suskind,Robert J. Webber,Sally Tannenbaum,Mary Ellen Nevins +7 more
TL;DR: Results partially support the notion that caregiver-directed language enrichment interventions can change home language environments of D/HH children from low-SES backgrounds, and further longitudinal studies are necessary.
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Beyond Walkers in Stochastic Quantum Chemistry: Reducing Error Using Fast Randomized Iteration.
TL;DR: Lim et al. as discussed by the authors introduced a family of methods for the full configuration interaction problem in quantum chemistry, based on the fast randomized iteration (FRI) framework, which stochastically impose sparsity during iterations of the power method and can be viewed as a generalization of FCIQMC without walkers.
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Maximizing Simulated Tropical Cyclone Intensity With Action Minimization
TL;DR: In this paper, an action minimization algorithm applied to the WRF and WRFPLUS models is introduced to better leverage computational resources for the study of rapid intensification, which is a distinguishing feature of many intense TCs.
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Development of the Survey of Parent/Provider Expectations and Knowledge (SPEAK):
Dana L. Suskind,Christy Y. Y. Leung,Robert J. Webber,Alison C. Hundertmark,Kristin R. Leffel,Elizabeth Suskind,Marc W. Hernandez,Eileen Graf +7 more
TL;DR: The Survey of Parent/Provider Expectations and Knowledge (SPEAK) as mentioned in this paper is a self-administered questionnaire assessing expectations and knowledge about early childhood cognitive and language development.
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Practical rare event sampling for extreme mesoscale weather.
TL;DR: In this paper, the authors present a new rare event sampling algorithm called quantile diffusion Monte Carlo (quantile DMC), which is a simple-to-use algorithm that can sample extreme tail behavior for a wide class of processes.